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  • Parallelism in .NET – Part 12, More on Task Decomposition

    - by Reed
    Many tasks can be decomposed using a Data Decomposition approach, but often, this is not appropriate.  Frequently, decomposing the problem into distinctive tasks that must be performed is a more natural abstraction. However, as I mentioned in Part 1, Task Decomposition tends to be a bit more difficult than data decomposition, and can require a bit more effort.  Before we being parallelizing our algorithm based on the tasks being performed, we need to decompose our problem, and take special care of certain considerations such as ordering and grouping of tasks. Up to this point in this series, I’ve focused on parallelization techniques which are most appropriate when a problem space can be decomposed by data.  Using PLINQ and the Parallel class, I’ve shown how problem spaces where there is a collection of data, and each element needs to be processed, can potentially be parallelized. However, there are many other routines where this is not appropriate.  Often, instead of working on a collection of data, there is a single piece of data which must be processed using an algorithm or series of algorithms.  Here, there is no collection of data, but there may still be opportunities for parallelism. As I mentioned before, in cases like this, the approach is to look at your overall routine, and decompose your problem space based on tasks.  The idea here is to look for discrete “tasks,” individual pieces of work which can be conceptually thought of as a single operation. Let’s revisit the example I used in Part 1, an application startup path.  Say we want our program, at startup, to do a bunch of individual actions, or “tasks”.  The following is our list of duties we must perform right at startup: Display a splash screen Request a license from our license manager Check for an update to the software from our web server If an update is available, download it Setup our menu structure based on our current license Open and display our main, welcome Window Hide the splash screen The first step in Task Decomposition is breaking up the problem space into discrete tasks. This, naturally, can be abstracted as seven discrete tasks.  In the serial version of our program, if we were to diagram this, the general process would appear as: These tasks, obviously, provide some opportunities for parallelism.  Before we can parallelize this routine, we need to analyze these tasks, and find any dependencies between tasks.  In this case, our dependencies include: The splash screen must be displayed first, and as quickly as possible. We can’t download an update before we see whether one exists. Our menu structure depends on our license, so we must check for the license before setting up the menus. Since our welcome screen will notify the user of an update, we can’t show it until we’ve downloaded the update. Since our welcome screen includes menus that are customized based off the licensing, we can’t display it until we’ve received a license. We can’t hide the splash until our welcome screen is displayed. By listing our dependencies, we start to see the natural ordering that must occur for the tasks to be processed correctly. The second step in Task Decomposition is determining the dependencies between tasks, and ordering tasks based on their dependencies. Looking at these tasks, and looking at all the dependencies, we quickly see that even a simple decomposition such as this one can get quite complicated.  In order to simplify the problem of defining the dependencies, it’s often a useful practice to group our tasks into larger, discrete tasks.  The goal when grouping tasks is that you want to make each task “group” have as few dependencies as possible to other tasks or groups, and then work out the dependencies within that group.  Typically, this works best when any external dependency is based on the “last” task within the group when it’s ordered, although that is not a firm requirement.  This process is often called Grouping Tasks.  In our case, we can easily group together tasks, effectively turning this into four discrete task groups: 1. Show our splash screen – This needs to be left as its own task.  First, multiple things depend on this task, mainly because we want this to start before any other action, and start as quickly as possible. 2. Check for Update and Download the Update if it Exists - These two tasks logically group together.  We know we only download an update if the update exists, so that naturally follows.  This task has one dependency as an input, and other tasks only rely on the final task within this group. 3. Request a License, and then Setup the Menus – Here, we can group these two tasks together.  Although we mentioned that our welcome screen depends on the license returned, it also depends on setting up the menu, which is the final task here.  Setting up our menus cannot happen until after our license is requested.  By grouping these together, we further reduce our problem space. 4. Display welcome and hide splash - Finally, we can display our welcome window and hide our splash screen.  This task group depends on all three previous task groups – it cannot happen until all three of the previous groups have completed. By grouping the tasks together, we reduce our problem space, and can naturally see a pattern for how this process can be parallelized.  The diagram below shows one approach: The orange boxes show each task group, with each task represented within.  We can, now, effectively take these tasks, and run a large portion of this process in parallel, including the portions which may be the most time consuming.  We’ve now created two parallel paths which our process execution can follow, hopefully speeding up the application startup time dramatically. The main point to remember here is that, when decomposing your problem space by tasks, you need to: Define each discrete action as an individual Task Discover dependencies between your tasks Group tasks based on their dependencies Order the tasks and groups of tasks

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  • Linux-Containers — Part 1: Overview

    - by Lenz Grimmer
    "Containers" by Jean-Pierre Martineau (CC BY-NC-SA 2.0). Linux Containers (LXC) provide a means to isolate individual services or applications as well as of a complete Linux operating system from other services running on the same host. To accomplish this, each container gets its own directory structure, network devices, IP addresses and process table. The processes running in other containers or the host system are not visible from inside a container. Additionally, Linux Containers allow for fine granular control of resources like RAM, CPU or disk I/O. Generally speaking, Linux Containers use a completely different approach than "classicial" virtualization technologies like KVM or Xen (on which Oracle VM Server for x86 is based on). An application running inside a container will be executed directly on the operating system kernel of the host system, shielded from all other running processes in a sandbox-like environment. This allows a very direct and fair distribution of CPU and I/O-resources. Linux containers can offer the best possible performance and several possibilities for managing and sharing the resources available. Similar to Containers (or Zones) on Oracle Solaris or FreeBSD jails, the same kernel version runs on the host as well as in the containers; it is not possible to run different Linux kernel versions or other operating systems like Microsoft Windows or Oracle Solaris for x86 inside a container. However, it is possible to run different Linux distribution versions (e.g. Fedora Linux in a container on top of an Oracle Linux host), provided it supports the version of the Linux kernel that runs on the host. This approach has one caveat, though - if any of the containers causes a kernel crash, it will bring down all other containers (and the host system) as well. For example, Oracle's Unbreakable Enterprise Kernel Release 2 (2.6.39) is supported for both Oracle Linux 5 and 6. This makes it possible to run Oracle Linux 5 and 6 container instances on top of an Oracle Linux 6 system. Since Linux Containers are fully implemented on the OS level (the Linux kernel), they can be easily combined with other virtualization technologies. It's certainly possible to set up Linux containers within a virtualized Linux instance that runs inside Oracle VM Server for Oracle VM Virtualbox. Some use cases for Linux Containers include: Consolidation of multiple separate Linux systems on one server: instances of Linux systems that are not performance-critical or only see sporadic use (e.g. a fax or print server or intranet services) do not necessarily need a dedicated server for their operations. These can easily be consolidated to run inside containers on a single server, to preserve energy and rack space. Running multiple instances of an application in parallel, e.g. for different users or customers. Each user receives his "own" application instance, with a defined level of service/performance. This prevents that one user's application could hog the entire system and ensures, that each user only has access to his own data set. It also helps to save main memory — if multiple instances of a same process are running, the Linux kernel can share memory pages that are identical and unchanged across all application instances. This also applies to shared libraries that applications may use, they are generally held in memory once and mapped to multiple processes. Quickly creating sandbox environments for development and testing purposes: containers that have been created and configured once can be archived as templates and can be duplicated (cloned) instantly on demand. After finishing the activity, the clone can safely be discarded. This allows to provide repeatable software builds and test environments, because the system will always be reset to its initial state for each run. Linux Containers also boot significantly faster than "classic" virtual machines, which can save a lot of time when running frequent build or test runs on applications. Safe execution of an individual application: if an application running inside a container has been compromised because of a security vulnerability, the host system and other containers remain unaffected. The potential damage can be minimized, analyzed and resolved directly from the host system. Note: Linux Containers on Oracle Linux 6 with the Unbreakable Enterprise Kernel Release 2 (2.6.39) are still marked as Technology Preview - their use is only recommended for testing and evaluation purposes. The Open-Source project "Linux Containers" (LXC) is driving the development of the technology behind this, which is based on the "Control Groups" (CGroups) and "Name Spaces" functionality of the Linux kernel. Oracle is actively involved in the Linux Containers development and contributes patches to the upstream LXC code base. Control Groups provide means to manage and monitor the allocation of resources for individual processes or process groups. Among other things, you can restrict the maximum amount of memory, CPU cycles as well as the disk and network throughput (in MB/s or IOP/s) that are available for an application. Name Spaces help to isolate process groups from each other, e.g. the visibility of other running processes or the exclusive access to a network device. It's also possible to restrict a process group's access and visibility of the entire file system hierarchy (similar to a classic "chroot" environment). CGroups and Name Spaces provide the foundation on which Linux containers are based on, but they can actually be used independently as well. A more detailed description of how Linux Containers can be created and managed on Oracle Linux will be explained in the second part of this article. Additional links related to Linux Containers: OTN Article: The Role of Oracle Solaris Zones and Linux Containers in a Virtualization Strategy Linux Containers on Wikipedia - Lenz Grimmer Follow me on: Personal Blog | Facebook | Twitter | Linux Blog |

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  • Oracle Enterprise Data Quality: Ever Integration-ready

    - by Mala Narasimharajan
    It is closing in on a year now since Oracle’s acquisition of Datanomic, and the addition of Oracle Enterprise Data Quality (EDQ) to the Oracle software family. The big move has caused some big shifts in emphasis and some very encouraging excitement from the field.  To give an illustration, combined with a shameless promotion of how EDQ can help to give quick insights into your data, I did a quick Phrase Profile of the subject field of emails to the Global EDQ mailing list since it was set up last September. The results revealed a very clear theme:   Integration, Integration, Integration! As well as the important Siebel and Oracle Data Integrator (ODI) integrations, we have been asked about integration with a huge variety of Oracle applications, including EBS, Peoplesoft, CRM on Demand, Fusion, DRM, Endeca, RightNow, and more - and we have not stood still! While it would not have been possible to develop specific pre-integrations with all of the above within a year, we have developed a package of feature-rich out-of-the-box web services and batch processes that can be plugged into any application or middleware technology with ease. And with Siebel, they work out of the box. Oracle Enterprise Data Quality version 9.0.4 includes the Customer Data Services (CDS) pack – a ready set of standard processes with standard interfaces, to provide integrated: Address verification and cleansing  Individual matching Organization matching The services can are suitable for either Batch or Real-Time processing, and are enabled for international data, with simple configuration options driving the set of locale-specific dictionaries that are used. For example, large dictionaries are provided to support international name transcription and variant matching, including highly specialized handling for Arabic, Japanese, Chinese and Korean data. In total across all locales, CDS includes well over a million dictionary entries.   Excerpt from EDQ’s CDS Individual Name Standardization Dictionary CDS has been developed to replace the OEM of Informatica Identity Resolution (IIR) for attached Data Quality on the Oracle price list, but does this in a way that creates a ‘best of both worlds’ situation for customers, who can harness not only the out-of-the-box functionality of pre-packaged matching and standardization services, but also the flexibility of OEDQ if they want to customize the interfaces or the process logic, without having to learn more than one product. From a competitive point of view, we believe this stands us in good stead against our key competitors, including Informatica, who have separate ‘Identity Resolution’ and general DQ products, and IBM, who provide limited out-of-the-box capabilities (with a steep learning curve) in both their QualityStage data quality and Initiate matching products. Here is a brief guide to the main services provided in the pack: Address Verification and Standardization EDQ’s CDS Address Cleaning Process The Address Verification and Standardization service uses EDQ Address Verification (an OEM of Loqate software) to verify and clean addresses in either real-time or batch. The Address Verification processor is wrapped in an EDQ process – this adds significant capabilities over calling the underlying Address Verification API directly, specifically: Country-specific thresholds to determine when to accept the verification result (and therefore to change the input address) based on the confidence level of the API Optimization of address verification by pre-standardizing data where required Formatting of output addresses into the input address fields normally used by applications Adding descriptions of the address verification and geocoding return codes The process can then be used to provide real-time and batch address cleansing in any application; such as a simple web page calling address cleaning and geocoding as part of a check on individual data.     Duplicate Prevention Unlike Informatica Identity Resolution (IIR), EDQ uses stateless services for duplicate prevention to avoid issues caused by complex replication and synchronization of large volume customer data. When a record is added or updated in an application, the EDQ Cluster Key Generation service is called, and returns a number of key values. These are used to select other records (‘candidates’) that may match in the application data (which has been pre-seeded with keys using the same service). The ‘driving record’ (the new or updated record) is then presented along with all selected candidates to the EDQ Matching Service, which decides which of the candidates are a good match with the driving record, and scores them according to the strength of match. In this model, complex multi-locale EDQ techniques can be used to generate the keys and ensure that the right balance between performance and matching effectiveness is maintained, while ensuring that the application retains control of data integrity and transactional commits. The process is explained below: EDQ Duplicate Prevention Architecture Note that where the integration is with a hub, there may be an additional call to the Cluster Key Generation service if the master record has changed due to merges with other records (and therefore needs to have new key values generated before commit). Batch Matching In order to allow customers to use different match rules in batch to real-time, separate matching templates are provided for batch matching. For example, some customers want to minimize intervention in key user flows (such as adding new customers) in front end applications, but to conduct a more exhaustive match on a regular basis in the back office. The batch matching jobs are also used when migrating data between systems, and in this case normally a more precise (and automated) type of matching is required, in order to minimize the review work performed by Data Stewards.  In batch matching, data is captured into EDQ using its standard interfaces, and records are standardized, clustered and matched in an EDQ job before matches are written out. As with all EDQ jobs, batch matching may be called from Oracle Data Integrator (ODI) if required. When working with Siebel CRM (or master data in Siebel UCM), Siebel’s Data Quality Manager is used to instigate batch jobs, and a shared staging database is used to write records for matching and to consume match results. The CDS batch matching processes automatically adjust to Siebel’s ‘Full Match’ (match all records against each other) and ‘Incremental Match’ (match a subset of records against all of their selected candidates) modes. The Future The Customer Data Services Pack is an important part of the Oracle strategy for EDQ, offering a clear path to making Data Quality Assurance an integral part of enterprise applications, and providing a strong value proposition for adopting EDQ. We are planning various additions and improvements, including: An out-of-the-box Data Quality Dashboard Even more comprehensive international data handling Address search (suggesting multiple results) Integrated address matching The EDQ Customer Data Services Pack is part of the Enterprise Data Quality Media Pack, available for download at http://www.oracle.com/technetwork/middleware/oedq/downloads/index.html.

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  • The Enterprise is a Curmudgeon

    - by John K. Hines
    Working in an enterprise environment is a unique challenge.  There's a lot more to software development than developing software.  A project lead or Scrum Master has to manage personalities and intra-team politics, has to manage accomplishing the task at hand while creating the opportunities and a reputation for handling desirable future work, has to create a competent, happy team that actually delivers while being careful not to burn bridges or hurt feelings outside the team.  Which makes me feel surprised to read advice like: " The enterprise should figure out what is likely to work best for itself and try to use it." - Ken Schwaber, The Enterprise and Scrum. The enterprises I have experience with are fundamentally unable to be self-reflective.  It's like asking a Roman gladiator if he'd like to carve out a little space in the arena for some silent meditation.  I'm currently wondering how compatible Scrum is with the top-down hierarchy of life in a large organization.  Specifically, manufacturing-mindset, fixed-release, harmony-valuing large organizations.  Now I understand why Agile can be a better fit for companies without much organizational inertia. Recently I've talked with nearly two dozen software professionals and their managers about Scrum and Agile.  I've become convinced that a developer, team, organization, or enterprise can be Agile without using Scrum.  But I'm not sure about what process would be the best fit, in general, for an enterprise that wants to become Agile.  It's possible I should read more than just the introduction to Ken's book. I do feel prepared to answer some of the questions I had asked in a previous post: How can Agile practices (including but not limited to Scrum) be adopted in situations where the highest-placed managers in a company demand software within extremely aggressive deadlines? Answer: In a very limited capacity at the individual level.  The situation here is that the senior management of this company values any software release more than it values developer well-being, end-user experience, or software quality.  Only if the developing organization is given an immediate refactoring opportunity does this sort of development make sense to a person who values sustainable software.   How can Agile practices be adopted by teams that do not perform a continuous cycle of new development, such as those whose sole purpose is to reproduce and debug customer issues? Answer: It depends.  For Scrum in particular, I don't believe Scrum is meant to manage unpredictable work.  While you can easily adopt XP practices for bug fixing, the project-management aspects of Scrum require some predictability.  My question here was meant toward those who want to apply Scrum to non-development teams.  In some cases it works, in others it does not. How can a team measure if its development efforts are both Agile and employ sound engineering practices? Answer: I'm currently leaning toward measuring these independently.  The Agile Principles are a terrific way to measure if a software team is agile.  Sound engineering practices are those practices which help developers meet the principles.  I think Scrum is being mistakenly applied as an engineering practice when it is essentially a project management practice.  In my opinion, XP and Lean are examples of good engineering practices. How can Agile be explained in an accurate way that describes its benefits to sceptical developers and/or revenue-focused non-developers? Answer: Agile techniques will result in higher-quality, lower-cost software development.  This comes primarily from finding defects earlier in the development cycle.  If there are individual developers who do not want to collaborate, write unit tests, or refactor, then these are simply developers who are either working in an area where adding these techniques will not add value (i.e. they are an expert) or they are a developer who is satisfied with the status quo.  In the first case they should be left alone.  In the second case, the results of Agile should be demonstrated by other developers who are willing to receive recognition for their efforts.  It all comes down to individuals, doesn't it?  If you're working in an organization whose Agile adoption consists exclusively of Scrum, consider ways to form individual Agile teams to demonstrate its benefits.  These can even be virtual teams that span people across org-chart boundaries.  Once you can measure real value, whether it's Scrum, Lean, or something else, people will follow.  Even the curmudgeons.

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  • SOA, Governance, and Drugs

    Why is IT governance important in service oriented architecture (SOA)? IT Governance provides a framework for making appropriate decisions based on company guidelines and accepted standards. This framework also outlines each stakeholder’s responsibilities and authority when making important architectural or design decisions. Furthermore, this framework of governance defines parameters and constraints that are used to give context and perspective when making decisions. The use of governance as it applies to SOA ensures that specific design principles and patterns are used when developing and maintaining services. When governance is consistently applied systems the following benefits are achieved according to Anne Thomas Manes in 2010. Governance makes sure that services conform to standard interface patterns, common data modeling practices, and promotes the incorporation of existing system functionality by building on top of other available services across a system. Governance defines development standards based on proven design principles and patterns that promote reuse and composition. Governance provides developers a set of proven design principles, standards and practices that promote the reduction in system based component dependencies.  By following these guidelines, individual components will be easier to maintain. For me personally, I am a fan of IT governance, and feel that it valuable part of any corporate IT department. However, depending on how it is implemented can really affect the value of using IT governance.  Companies need to find a way to ensure that governance does not become extreme in its policies and procedures. I know for me personally, I would really dislike working under a completely totalitarian or laissez-faire version of governance. Developers need to be able to be creative in their designs and too much governance can really impede the design process and prevent the most optimal design from being developed. On the other hand, with no governance enforced, no standards will be followed and accepted design patterns will be ignored. I have personally had to spend a lot of time working on this particular scenario and I have found that the concept of code reuse and composition is almost nonexistent.  Based on this, too much time and money is wasted on redeveloping existing aspects of an application that already exist within the system as a whole. I think moving forward we will see a staggered form of IT governance, regardless if it is for SOA or IT in general.  Depending on the size of a company and the size of its IT department,  I can see IT governance as a layered approach in that the top layer will be defined by enterprise architects that focus on abstract concepts pertaining to high level design, general  guidelines, acceptable best practices, and recommended design patterns.  The next layer will be defined by solution architects or department managers that further expand on abstracted guidelines defined by the enterprise architects. This layer will contain further definitions as to when various design patterns, coding standards, and best practices are to be applied based on the context of the solutions that are being developed by the department. The final layer will be defined by the system designer or a solutions architect assed to a project in that they will define what design patterns will be used in a solution, naming conventions, as well as outline how a system will function based on the best practices defined by the previous layers. This layered approach allows for IT departments to be flexible in that system designers have creative leeway in designing solutions to meet the needs of the business, but they must operate within the confines of the abstracted IT governance guidelines.  A real world example of this can be seen in the United States as it pertains to governance of the people in that the US government defines rules and regulations in the abstract and then the state governments take these guidelines and applies them based on the will of the people in each individual state. Furthermore, the county or city governments are the ones that actually enforce these rules based on how they are interpreted by local community.  To further define my example, the United States government defines that marijuana is illegal. Each individual state has the option to determine this regulation as it wishes in that the state of Florida determines that all uses of the drug are illegal, but the state of California legally allows the use of marijuana for medicinal purposes only. Based on these accepted practices each local government enforces these rules in that a police officer will arrest anyone in the state of Florida for having this drug on them if they walk down the street, but in California if a person has a medical prescription for the drug they will not get arrested.  REFERENCESThomas Manes, Anne. (2010). Understanding SOA Governance: http://www.soamag.com/I40/0610-2.php

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  • Where Next for Google Translate? And What of Information Quality?

    - by ultan o'broin
    Fascinating article in the UK Guardian newspaper called Can Google break the computer language barrier? In it, Andreas Zollman, who works on Google Translate, comments that the quality of Google Translate's output relative to the amount of data required to create that output is clearly now falling foul of the law of diminishing returns. He says: "Each doubling of the amount of translated data input led to about a 0.5% improvement in the quality of the output," he suggests, but the doublings are not infinite. "We are now at this limit where there isn't that much more data in the world that we can use," he admits. "So now it is much more important again to add on different approaches and rules-based models." The Translation Guy has a further discussion on this, called Google Translate is Finished. He says: "And there aren't that many doublings left, if any. I can't say how much text Google has assimilated into their machine translation databases, but it's been reported that they have scanned about 11% of all printed content ever published. So double that, and double it again, and once more, shoveling all that into the translation hopper, and pretty soon you get the sum of all human knowledge, which means a whopping 1.5% improvement in the quality of the engines when everything has been analyzed. That's what we've got to look forward to, at best, since Google spiders regularly surf the Web, which in its vastness dwarfs all previously published content. So to all intents and purposes, the statistical machine translation tools of Google are done. Outstanding job, Googlers. Thanks." Surprisingly, all this analysis hasn't raised that much comment from the fans of machine translation, or its detractors either for that matter. Perhaps, it's the season of goodwill? What is clear to me, however, of course is that Google Translate isn't really finished (in any sense of the word). I am sure Google will investigate and come up with new rule-based translation models to enhance what they have already and that will also scale effectively where others didn't. So too, will they harness human input, which really is the way to go to train MT in the quality direction. But that aside, what does it say about the quality of the data that is being used for statistical machine translation in the first place? From the Guardian article it's clear that a huge humanly translated corpus drove the gains for Google Translate and now what's left is the dregs of badly translated and poorly created source materials that just can't deliver quality translations. There's a message about information quality there, surely. In the enterprise applications space, where we have some control over content this whole debate reinforces the relationship between information quality at source and translation efficiency, regardless of the technology used to do the translation. But as more automation comes to the fore, that information quality is even more critical if you want anything approaching a scalable solution. This is important for user experience professionals. Issues like user generated content translation, multilingual personalization, and scalable language quality are central to a superior global UX; it's a competitive issue we cannot ignore.

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  • Using the StopWatch class to calculate the execution time of a block of code

    - by vik20000in
      Many of the times while doing the performance tuning of some, class, webpage, component, control etc. we first measure the current time taken in the execution of that code. This helps in understanding the location in code which is actually causing the performance issue and also help in measuring the amount of improvement by making the changes. This measurement is very important as it helps us understand the problem in code, Helps us to write better code next time (as we have already learnt what kind of improvement can be made with different code) . Normally developers create 2 objects of the DateTime class. The exact time is collected before and after the code where the performance needs to be measured.  Next the difference between the two objects is used to know about the time spent in the code that is measured. Below is an example of the sample code.             DateTime dt1, dt2;             dt1 = DateTime.Now;             for (int i = 0; i < 1000000; i++)             {                 string str = "string";             }             dt2 = DateTime.Now;             TimeSpan ts = dt2.Subtract(dt1);             Console.WriteLine("Time Spent : " + ts.TotalMilliseconds.ToString());   The above code works great. But the dot net framework also provides for another way to capture the time spent on the code without doing much effort (creating 2 datetime object, timespan object etc..). We can use the inbuilt StopWatch class to get the exact time spent. Below is an example of the same work with the help of the StopWatch class.             Stopwatch sw = Stopwatch.StartNew();             for (int i = 0; i < 1000000; i++)             {                 string str = "string";             }             sw.Stop();             Console.WriteLine("Time Spent : " +sw.Elapsed.TotalMilliseconds.ToString());   [Note the StopWatch class resides in the System.Diagnostics namespace] If you use the StopWatch class the time taken for measuring the performance is much better, with very little effort. Vikram

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  • SPARC T4-2 Produces World Record Oracle Essbase Aggregate Storage Benchmark Result

    - by Brian
    Significance of Results Oracle's SPARC T4-2 server configured with a Sun Storage F5100 Flash Array and running Oracle Solaris 10 with Oracle Database 11g has achieved exceptional performance for the Oracle Essbase Aggregate Storage Option benchmark. The benchmark has upwards of 1 billion records, 15 dimensions and millions of members. Oracle Essbase is a multi-dimensional online analytical processing (OLAP) server and is well-suited to work well with SPARC T4 servers. The SPARC T4-2 server (2 cpus) running Oracle Essbase 11.1.2.2.100 outperformed the previous published results on Oracle's SPARC Enterprise M5000 server (4 cpus) with Oracle Essbase 11.1.1.3 on Oracle Solaris 10 by 80%, 32% and 2x performance improvement on Data Loading, Default Aggregation and Usage Based Aggregation, respectively. The SPARC T4-2 server with Sun Storage F5100 Flash Array and Oracle Essbase running on Oracle Solaris 10 achieves sub-second query response times for 20,000 users in a 15 dimension database. The SPARC T4-2 server configured with Oracle Essbase was able to aggregate and store values in the database for a 15 dimension cube in 398 minutes with 16 threads and in 484 minutes with 8 threads. The Sun Storage F5100 Flash Array provides more than a 20% improvement out-of-the-box compared to a mid-size fiber channel disk array for default aggregation and user-based aggregation. The Sun Storage F5100 Flash Array with Oracle Essbase provides the best combination for large Oracle Essbase databases leveraging Oracle Solaris ZFS and taking advantage of high bandwidth for faster load and aggregation. Oracle Fusion Middleware provides a family of complete, integrated, hot pluggable and best-of-breed products known for enabling enterprise customers to create and run agile and intelligent business applications. Oracle Essbase's performance demonstrates why so many customers rely on Oracle Fusion Middleware as their foundation for innovation. Performance Landscape System Data Size(millions of items) Database Load(minutes) Default Aggregation(minutes) Usage Based Aggregation(minutes) SPARC T4-2, 2 x SPARC T4 2.85 GHz 1000 149 398* 55 Sun M5000, 4 x SPARC64 VII 2.53 GHz 1000 269 526 115 Sun M5000, 4 x SPARC64 VII 2.4 GHz 400 120 448 18 * – 398 mins with CALCPARALLEL set to 16; 484 mins with CALCPARALLEL threads set to 8 Configuration Summary Hardware Configuration: 1 x SPARC T4-2 2 x 2.85 GHz SPARC T4 processors 128 GB memory 2 x 300 GB 10000 RPM SAS internal disks Storage Configuration: 1 x Sun Storage F5100 Flash Array 40 x 24 GB flash modules SAS HBA with 2 SAS channels Data Storage Scheme Striped - RAID 0 Oracle Solaris ZFS Software Configuration: Oracle Solaris 10 8/11 Installer V 11.1.2.2.100 Oracle Essbase Client v 11.1.2.2.100 Oracle Essbase v 11.1.2.2.100 Oracle Essbase Administration services 64-bit Oracle Database 11g Release 2 (11.2.0.3) HP's Mercury Interactive QuickTest Professional 9.5.0 Benchmark Description The objective of the Oracle Essbase Aggregate Storage Option benchmark is to showcase the ability of Oracle Essbase to scale in terms of user population and data volume for large enterprise deployments. Typical administrative and end-user operations for OLAP applications were simulated to produce benchmark results. The benchmark test results include: Database Load: Time elapsed to build a database including outline and data load. Default Aggregation: Time elapsed to build aggregation. User Based Aggregation: Time elapsed of the aggregate views proposed as a result of tracked retrieval queries. Summary of the data used for this benchmark: 40 flat files, each of size 1.2 GB, 49.4 GB in total 10 million rows per file, 1 billion rows total 28 columns of data per row Database outline has 15 dimensions (five of them are attribute dimensions) Customer dimension has 13.3 million members 3 rule files Key Points and Best Practices The Sun Storage F5100 Flash Array has been used to accelerate the application performance. Setting data load threads (DLTHREADSPREPARE) to 64 and Load Buffer to 6 improved dataloading by about 9%. Factors influencing aggregation materialization performance are "Aggregate Storage Cache" and "Number of Threads" (CALCPARALLEL) for parallel view materialization. The optimal values for this workload on the SPARC T4-2 server were: Aggregate Storage Cache: 32 GB CALCPARALLEL: 16   See Also Oracle Essbase Aggregate Storage Option Benchmark on Oracle's SPARC T4-2 Server oracle.com Oracle Essbase oracle.com OTN SPARC T4-2 Server oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN Disclosure Statement Copyright 2012, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 28 August 2012.

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  • A tiny Utility to recycle an IIS Application Pool

    - by Rick Strahl
    In the last few weeks I've annoyingly been having problems with an area on my Web site. It's basically ancient articles that are using ASP classic pages and for reasons unknown ASP classic locks up on these pages frequently. It's not an individual page, but ALL ASP classic pages lock up. Ah yes, gotta old tech gone bad. It's not super critical since the content is really old, but still a hassle since it's linked content that still gets quite a bit of traffic. When it happens all ASP classic in that AppPool dies. I've been having a hard time tracking this one down - I suspect an errant COM object I have a Web Monitor running on the server that's checking for failures and while the monitor can detect the failures when the timeouts occur, I didn't have a good way to just restart that particular application pool. I started putzing around with PowerShell, but - as so often seems the case - I can never get the PowerShell syntax right - I just don't use it enough and have to dig out cheat sheets etc. In any case, after about 20 minutes of that I decided to just create a small .NET Console Application that does the trick instead, and in a few minutes I had this:using System; using System.Collections.Generic; using System.Text; using System.DirectoryServices; namespace RecycleApplicationPool { class Program { static void Main(string[] args) { string appPoolName = "DefaultAppPool"; string machineName = "LOCALHOST"; if (args.Length > 0) appPoolName = args[0]; if (args.Length > 1) machineName = args[1]; string error = null; DirectoryEntry root = null; try { Console.WriteLine("Restarting Application Pool " + appPoolName + " on " + machineName + "..."); root = new DirectoryEntry("IIS://" + machineName + "/W3SVC/AppPools/" +appPoolName); Console.WriteLine(root.InvokeGet("Name")); root.Invoke("Recycle"); Console.WriteLine("Application Pool recycling complete..."); } catch(Exception ex) { error = "Error: Unable to access AppPool: " + ex.Message; } if ( !string.IsNullOrEmpty(error) ) { Console.WriteLine(error); return; } } } } To run in you basically provide the name of the ApplicationPool and optionally a machine name if it's not on the local box. RecyleApplicationPool.exe "WestWindArticles" And off it goes. What's nice about AppPool recycling versus doing a full IISRESET is that it only affects the AppPool, and more importantly AppPool recycles happen in a staggered fashion - the existing instance isn't shut down immediately until requests finish while a new instance is fired up to handle new requests. So, now I can easily plug this Executable into my West Wind Web Monitor as an action to take when the site is not responding or timing out which is a big improvement than hanging for an unspecified amount of time. I'm posting this fairly trivial bit of code just in case somebody (maybe myself a few months down the road) is searching for ApplicationPool recyling code. It's clearly trivial, but I've written batch files for this a bunch of times before and actually having a small utility around without having to worry whether Powershell is installed and configured right is actually an improvement. Next time I think about using PowerShell remind me that it's just easier to just build a small .NET Console app, 'k? :-) Resources Download Executable and VS Project© Rick Strahl, West Wind Technologies, 2005-2012Posted in IIS7  .NET  Windows   Tweet !function(d,s,id){var js,fjs=d.getElementsByTagName(s)[0];if(!d.getElementById(id)){js=d.createElement(s);js.id=id;js.src="//platform.twitter.com/widgets.js";fjs.parentNode.insertBefore(js,fjs);}}(document,"script","twitter-wjs"); (function() { var po = document.createElement('script'); po.type = 'text/javascript'; po.async = true; po.src = 'https://apis.google.com/js/plusone.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(po, s); })();

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  • How to get bearable 2D and 3D performance on AMD Radeon HD 6950?

    - by l0b0
    I have had an AMD Radeon HD 6950 (i.e., Cayman series) for a couple years now, and I have tried a lot of combinations of drivers and settings with terrible results. I'm completely at a loss as to how to proceed. The open source driver has much better 2D performance, but it offloads all OpenGL rendering to the CPU. What I've tried so far: All the latest stable Ubuntu releases in the period, plus one Linux Mint release. All the latest stable AMD Catalyst Proprietary Display Drivers, and currently 13.1. The unofficial wiki installation instructions for every Ubuntu version and the semi-official Ubuntu instructions. All the tips and tweaks I could find for Minecraft (Optifine, reducing settings to minimum), VLC (postprocessing at minimum, rendering at native video size), Catalyst Control Center (flipped every lever in there) and X11 (some binary toggles I can no longer remember). Results: Typically 13-15 FPS in Minecraft, 30 max (100+ in Windows with the same driver version). Around 10 FPS in Team Fortress 2 using the official Steam client. Choppy video playback, in Flash and with VLC. CPU use goes through the roof when rendering video (150% for 1080p on YouTube in Chromium, 100% for 1080p H264 in VLC). glxgears shows 12.5 FPS when maximized. fgl_glxgears shows 10 FPS when maximized. Hardware details from lshw: Motherboard ASUS P6X58D-E CPU Intel Core i7 CPU 950 @ 3.07GHz (never overclocked; 64 bit) 6 GB RAM Video card product "Cayman PRO [Radeon HD 6950]", vendor "Hynix Semiconductor (Hyundai Electronics)" 2 x 1920x1200 monitors, both connected with HDMI. I feel I must be missing something absolutely fundamental here. Is there no accelerated support for anything on 64-bit architectures? Does a dual monitor completely mess up the driver? $ fglrxinfo display: :0 screen: 0 OpenGL vendor string: Advanced Micro Devices, Inc. OpenGL renderer string: AMD Radeon HD 6900 Series OpenGL version string: 4.2.11995 Compatibility Profile Context $ glxinfo | grep 'direct rendering' direct rendering: Yes I am currently using the open source driver, with the following results: Full frame rate and low CPU load when playing 1080p video. Black screen (but music in the background) in Team Fortress 2. Similar performance in Minecraft as the Catalyst driver. In hindsight obvious, since both end up offloading the rendering to the CPU. My /var/log/Xorg.0.log after upgrading to AMD Catalyst 13.1. Some possibly important lines: (WW) Falling back to old probe method for fglrx (WW) fglrx: No matching Device section for instance (BusID PCI:0@3:0:1) found The generated xorg.conf. The disabled "monitor" 0-DFP9 is actually an A/V receiver, which sometimes confuses the monitor drivers when turned on/off (but not in Windows). All three "monitor" devices are connected with HDMI. Edit: Chris Carter's suggestion to use the xorg-edgers PPA (Catalyst 13.1) resulted in some improvement, but still pretty bad performance overall: Minecraft stabilizes at 13-17 FPS, but at least the CPU load is "only" at 45-60%. Still 150% CPU use for 1080p video rendering on YouTube in Chromium. Massive improvement for 1080p H264 in VLC: 40-50% CPU use and no visible jitter glxgears performance about doubled to 25-30 FPS when maximized. fgl_glxgears still at ~10 FPS when maximized.

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  • Why Ultra-Low Power Computing Will Change Everything

    - by Tori Wieldt
    The ARM TechCon keynote "Why Ultra-Low Power Computing Will Change Everything" was anything but low-powered. The speaker, Dr. Johnathan Koomey, knows his subject: he is a Consulting Professor at Stanford University, worked for more than two decades at Lawrence Berkeley National Laboratory, and has been a visiting professor at Stanford University, Yale University, and UC Berkeley's Energy and Resources Group. His current focus is creating a standard (computations per kilowatt hour) and measuring computer energy consumption over time. The trends are impressive: energy consumption has halved every 1.5 years for the last 60 years. Battery life has made roughly a 10x improvement each decade since 1960. It's these improvements that have made laptops and cell phones possible. What does the future hold? Dr. Koomey said that in the past, the race by chip manufacturers was to create the fastest computer, but the priorities have now changed. New computers are tiny, smart, connected and cheap. "You can't underestimate the importance of a shift in industry focus from raw performance to power efficiency for mobile devices," he said. There is also a confluence of trends in computing, communications, sensors, and controls. The challenge is how to reduce the power requirements for these tiny devices. Alternate sources of power that are being explored are light, heat, motion, and even blood sugar. The University of Michigan has produced a miniature sensor that harnesses solar energy and could last for years without needing to be replaced. Also, the University of Washington has created a sensor that scavenges power from existing radio and TV signals.Specific devices designed for a purpose are much more efficient than general purpose computers. With all these sensors, instead of big data, developers should focus on nano-data, personalized information that will adjust the lights in a room, a machine, a variable sign, etc.Dr. Koomey showed some examples:The Proteus Digital Health Feedback System, an ingestible sensor that transmits when a patient has taken their medicine and is powered by their stomach juices. (Gives "powered by you" a whole new meaning!) Streetline Parking Systems, that provide real-time data about available parking spaces. The information can be sent to your phone or update parking signs around the city to point to areas with available spaces. Less driving around looking for parking spaces!The BigBelly trash system that uses solar power, compacts trash, and sends a text message when it is full. This dramatically reduces the number of times a truck has to come to pick up trash, freeing up resources and slashing fuel costs. This is a classic example of the efficiency of moving "bits not atoms." But researchers are approaching the physical limits of sensors, Dr. Kommey explained. With the current rate of technology improvement, they'll reach the three-atom transistor by 2041. Once they hit that wall, it will force a revolution they way we do computing. But wait, researchers at Purdue University and the University of New South Wales are both working on a reliable one-atom transistors! Other researchers are working on "approximate computing" that will reduce computing requirements drastically. So it's unclear where the wall actually is. In the meantime, as Dr. Koomey promised, ultra-low power computing will change everything.

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  • Drinking Our Own Champagne: Fusion Accounting Hub at Oracle

    - by Di Seghposs
    A guest post by Corey West, Senior Vice President, Oracle's Corporate Controller and Chief Accounting Officer There's no better story to tell than one about Oracle using its own products with blowout success. Here's how this one goes. As you know, Oracle has increased its share of the software market through a number of high-profile acquisitions. Legally combining companies is a very complicated process -- it can take months to complete, especially for the acquisitions with offices in several countries, each with its own unique laws and regulations. It's a mission critical and time sensitive process to roll an acquired company's legacy systems (running vital operations, such as accounts receivable and general ledger (GL)) into the existing systems at Oracle. To date, we've run our primary financial ledgers in E-Business Suite R12 -- and we've successfully met the requirements of the business and closed the books on time every single quarter. But there's always room for improvement and that comes in the form of Fusion Applications. We are now live on Fusion Accounting Hub (FAH), which is the first critical step in moving to a full Fusion Financials instance. We started with FAH so that we could design a global chart of accounts. Eventually, every transaction in every country will originate from this global chart of accounts -- it becomes the structure for managing our business more uniformly. In conjunction, we're using Oracle Hyperion Data Relationship Management (DRM) to centralize and automate governance of our global chart of accounts and related hierarchies, which will help us lower our costs and greatly reduce risk. Each month, we have to consolidate data from our primary general ledgers. We have been able to simplify this process considerably using FAH. We can now submit our primary ledgers running in E-Business Suite (EBS) R12 directly to FAH, eliminating the need for more than 90 redundant consolidation ledgers. Also we can submit incrementally, so if we need to book an adjustment in a primary ledger after close, we can do so without re-opening it and re-submitting. As a result, we have earlier visibility to period-end actuals during the close. A goal of this implementation, and one that we successfully achieved, is that we are able to use FAH globally with no customization. This means we have the ability to fully deploy ledger sets at the consolidation level, plus we can use standard functionality for currency translation and mass allocations. We're able to use account monitoring and drill down functionality from the consolidation level all the way through to EBS primary ledgers and sub-ledgers, which allows someone to click through a transaction appearing at the consolidation level clear through to its original source, a significant productivity enhancement when doing research. We also see a significant improvement in reporting using Essbase cube and Hyperion Smart View. Specifically, "the addition of an Essbase cube on top of the GL gives us tremendous versatility to automate and speed our elimination process," says Claire Sebti, Senior Director of Corporate Accounting at Oracle. A highlight of this story is that FAH is running in a co-existence environment. Our plan is to move to Fusion Financials in steps, starting with FAH. Next, our Oracle Financial Services Software subsidiary will move to a full Fusion Financials instance. Then we'll replace our EBS instance with Fusion Financials. This approach allows us to plan in steps, learn as we go, and not overwhelm our teams. It also reduces the risk that comes with moving the entire instance at once. Maria Smith, Vice President of Global Controller Operations, is confident about how they've positioned themselves to uptake more Fusion functionality and is eager to "continue to drive additional efficiency and cost savings." In this story, the happy customers are Oracle controllers, financial analysts, accounting specialists, and our management team that get earlier access to more flexible reporting. "Fusion Accounting Hub simplifies our processes and gives us more transparency into account activity," raves Alex SanJuan, Senior Director, Record to Report Strategic Process Owner. Overall, the team has been very impressed with the usability and functionality of FAH and are pleased with the quantifiable improvements. Claire Sebti states, "Our WD5 close activities have been reduced by at least four hours of system processing time, just for the consolidation group." Fusion Accounting Hub is an inspiring beginning to our Fusion Financials implementation story. There's no doubt it's going to be an international bestseller! Corey West, Senior Vice President Oracle's Corporate Controller and Chief Accounting Officer

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  • Columbus Regional Airport Authority Cuts Unbudgeted Carryover Costs for Capital Projects by 88% in One Year

    - by Melissa Centurio Lopes
    Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} The Columbus Regional Airport Authority (CRAA) is a public entity that works to connect Central Ohio with the world. It oversees operations at three airports?Port Columbus International Airport, Rickenbacker International Airport, and Bolton Field Airport?and manages the Rickenbacker Inland Port and Foreign Trade Zone # 138. It was created in 2002 through the merger of the Columbus Airport Authority and Rickenbacker Port Authority. CRAA manages approximately 100 projects annually, including initiatives as diverse as road and runway construction and maintenance, terminal improvements, construction of a new air traffic control tower, technology infrastructure development, customer service projects, and energy conservation programs. CRAA deployed Oracle’s Primavera P6 Enterprise Project Portfolio Management to create a unified methodology for scheduling and capital cash flow management. Today, the organization manages schedules and costs for all of its capital projects by using Primavera to provide enterprise wide visibility. As a result, CRAA cut unbudgeted carryover costs from US$24.4 million in 2010 to US$3.5 million in 2011?an 88% improvement. "Oracle’s Primavera P6 and Primavera Contract Management are transforming project management at CRAA. We have enabled resource-loaded scheduling and expanded visibility into cash flow, which allowed us to reduce unbudgeted carryover by 88% in a single year.” – Alex Beaver, Manager, Project Controls Office, Columbus Regional Airport Authority Challenges Standardize project planning and management for the approximately 100 projects?including airport terminal upgrades to road and runway creation and rehabilitation?that the airport authority undertakes annually Improve control over project scheduling and budgets to reduce unplanned carryover costs from one fiscal year to the next Ensure on-time, on-budget completion of critical infrastructure projects that support the organization’s mission to connect Central Ohio with the world through its three airports and inland port Solutions · Used Primavera P6 Enterprise Project Portfolio Management to develop a unified methodology for scheduling and managing capital projects for the airport authority, including the organization’s largest capital project ever?a five-year runway construction project · Gained a single, consolidated view into the organization’s capital projects and the ability to drill down into resource-loaded schedules and cash flow, enabling CRAA to take action earlier to avert the impact of emerging issues?including budget overages and project delays · Cut unbudgeted carryover costs from US$24.4 million in 2010 to US$3.5 million in 2011?an 88% improvement Click here to view all of the solutions. “Oracle’s Primavera solutions are the industry standard for project management. They provide robust and proven functionality that give us the power to effectively schedule and manage budgets for a wide range of projects, from terminal maintenance, to runway work, to golf course redesign,” said Alex Beaver, manager, project controls office, Columbus Regional Airport Authority. Click here to read the full version of the customer success story.

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  • Windows Azure Service Bus Splitter and Aggregator

    - by Alan Smith
    This article will cover basic implementations of the Splitter and Aggregator patterns using the Windows Azure Service Bus. The content will be included in the next release of the “Windows Azure Service Bus Developer Guide”, along with some other patterns I am working on. I’ve taken the pattern descriptions from the book “Enterprise Integration Patterns” by Gregor Hohpe. I bought a copy of the book in 2004, and recently dusted it off when I started to look at implementing the patterns on the Windows Azure Service Bus. Gregor has also presented an session in 2011 “Enterprise Integration Patterns: Past, Present and Future” which is well worth a look. I’ll be covering more patterns in the coming weeks, I’m currently working on Wire-Tap and Scatter-Gather. There will no doubt be a section on implementing these patterns in my “SOA, Connectivity and Integration using the Windows Azure Service Bus” course. There are a number of scenarios where a message needs to be divided into a number of sub messages, and also where a number of sub messages need to be combined to form one message. The splitter and aggregator patterns provide a definition of how this can be achieved. This section will focus on the implementation of basic splitter and aggregator patens using the Windows Azure Service Bus direct programming model. In BizTalk Server receive pipelines are typically used to implement the splitter patterns, with sequential convoy orchestrations often used to aggregate messages. In the current release of the Service Bus, there is no functionality in the direct programming model that implements these patterns, so it is up to the developer to implement them in the applications that send and receive messages. Splitter A message splitter takes a message and spits the message into a number of sub messages. As there are different scenarios for how a message can be split into sub messages, message splitters are implemented using different algorithms. The Enterprise Integration Patterns book describes the splatter pattern as follows: How can we process a message if it contains multiple elements, each of which may have to be processed in a different way? Use a Splitter to break out the composite message into a series of individual messages, each containing data related to one item. The Enterprise Integration Patterns website provides a description of the Splitter pattern here. In some scenarios a batch message could be split into the sub messages that are contained in the batch. The splitting of a message could be based on the message type of sub-message, or the trading partner that the sub message is to be sent to. Aggregator An aggregator takes a stream or related messages and combines them together to form one message. The Enterprise Integration Patterns book describes the aggregator pattern as follows: How do we combine the results of individual, but related messages so that they can be processed as a whole? Use a stateful filter, an Aggregator, to collect and store individual messages until a complete set of related messages has been received. Then, the Aggregator publishes a single message distilled from the individual messages. The Enterprise Integration Patterns website provides a description of the Aggregator pattern here. A common example of the need for an aggregator is in scenarios where a stream of messages needs to be combined into a daily batch to be sent to a legacy line-of-business application. The BizTalk Server EDI functionality provides support for batching messages in this way using a sequential convoy orchestration. Scenario The scenario for this implementation of the splitter and aggregator patterns is the sending and receiving of large messages using a Service Bus queue. In the current release, the Windows Azure Service Bus currently supports a maximum message size of 256 KB, with a maximum header size of 64 KB. This leaves a safe maximum body size of 192 KB. The BrokeredMessage class will support messages larger than 256 KB; in fact the Size property is of type long, implying that very large messages may be supported at some point in the future. The 256 KB size restriction is set in the service bus components that are deployed in the Windows Azure data centers. One of the ways of working around this size restriction is to split large messages into a sequence of smaller sub messages in the sending application, send them via a queue, and then reassemble them in the receiving application. This scenario will be used to demonstrate the pattern implementations. Implementation The splitter and aggregator will be used to provide functionality to send and receive large messages over the Windows Azure Service Bus. In order to make the implementations generic and reusable they will be implemented as a class library. The splitter will be implemented in the LargeMessageSender class and the aggregator in the LargeMessageReceiver class. A class diagram showing the two classes is shown below. Implementing the Splitter The splitter will take a large brokered message, and split the messages into a sequence of smaller sub-messages that can be transmitted over the service bus messaging entities. The LargeMessageSender class provides a Send method that takes a large brokered message as a parameter. The implementation of the class is shown below; console output has been added to provide details of the splitting operation. public class LargeMessageSender {     private static int SubMessageBodySize = 192 * 1024;     private QueueClient m_QueueClient;       public LargeMessageSender(QueueClient queueClient)     {         m_QueueClient = queueClient;     }       public void Send(BrokeredMessage message)     {         // Calculate the number of sub messages required.         long messageBodySize = message.Size;         int nrSubMessages = (int)(messageBodySize / SubMessageBodySize);         if (messageBodySize % SubMessageBodySize != 0)         {             nrSubMessages++;         }           // Create a unique session Id.         string sessionId = Guid.NewGuid().ToString();         Console.WriteLine("Message session Id: " + sessionId);         Console.Write("Sending {0} sub-messages", nrSubMessages);           Stream bodyStream = message.GetBody<Stream>();         for (int streamOffest = 0; streamOffest < messageBodySize;             streamOffest += SubMessageBodySize)         {                                     // Get the stream chunk from the large message             long arraySize = (messageBodySize - streamOffest) > SubMessageBodySize                 ? SubMessageBodySize : messageBodySize - streamOffest;             byte[] subMessageBytes = new byte[arraySize];             int result = bodyStream.Read(subMessageBytes, 0, (int)arraySize);             MemoryStream subMessageStream = new MemoryStream(subMessageBytes);               // Create a new message             BrokeredMessage subMessage = new BrokeredMessage(subMessageStream, true);             subMessage.SessionId = sessionId;               // Send the message             m_QueueClient.Send(subMessage);             Console.Write(".");         }         Console.WriteLine("Done!");     }} The LargeMessageSender class is initialized with a QueueClient that is created by the sending application. When the large message is sent, the number of sub messages is calculated based on the size of the body of the large message. A unique session Id is created to allow the sub messages to be sent as a message session, this session Id will be used for correlation in the aggregator. A for loop in then used to create the sequence of sub messages by creating chunks of data from the stream of the large message. The sub messages are then sent to the queue using the QueueClient. As sessions are used to correlate the messages, the queue used for message exchange must be created with the RequiresSession property set to true. Implementing the Aggregator The aggregator will receive the sub messages in the message session that was created by the splitter, and combine them to form a single, large message. The aggregator is implemented in the LargeMessageReceiver class, with a Receive method that returns a BrokeredMessage. The implementation of the class is shown below; console output has been added to provide details of the splitting operation.   public class LargeMessageReceiver {     private QueueClient m_QueueClient;       public LargeMessageReceiver(QueueClient queueClient)     {         m_QueueClient = queueClient;     }       public BrokeredMessage Receive()     {         // Create a memory stream to store the large message body.         MemoryStream largeMessageStream = new MemoryStream();           // Accept a message session from the queue.         MessageSession session = m_QueueClient.AcceptMessageSession();         Console.WriteLine("Message session Id: " + session.SessionId);         Console.Write("Receiving sub messages");           while (true)         {             // Receive a sub message             BrokeredMessage subMessage = session.Receive(TimeSpan.FromSeconds(5));               if (subMessage != null)             {                 // Copy the sub message body to the large message stream.                 Stream subMessageStream = subMessage.GetBody<Stream>();                 subMessageStream.CopyTo(largeMessageStream);                   // Mark the message as complete.                 subMessage.Complete();                 Console.Write(".");             }             else             {                 // The last message in the sequence is our completeness criteria.                 Console.WriteLine("Done!");                 break;             }         }                     // Create an aggregated message from the large message stream.         BrokeredMessage largeMessage = new BrokeredMessage(largeMessageStream, true);         return largeMessage;     } }   The LargeMessageReceiver initialized using a QueueClient that is created by the receiving application. The receive method creates a memory stream that will be used to aggregate the large message body. The AcceptMessageSession method on the QueueClient is then called, which will wait for the first message in a message session to become available on the queue. As the AcceptMessageSession can throw a timeout exception if no message is available on the queue after 60 seconds, a real-world implementation should handle this accordingly. Once the message session as accepted, the sub messages in the session are received, and their message body streams copied to the memory stream. Once all the messages have been received, the memory stream is used to create a large message, that is then returned to the receiving application. Testing the Implementation The splitter and aggregator are tested by creating a message sender and message receiver application. The payload for the large message will be one of the webcast video files from http://www.cloudcasts.net/, the file size is 9,697 KB, well over the 256 KB threshold imposed by the Service Bus. As the splitter and aggregator are implemented in a separate class library, the code used in the sender and receiver console is fairly basic. The implementation of the main method of the sending application is shown below.   static void Main(string[] args) {     // Create a token provider with the relevant credentials.     TokenProvider credentials =         TokenProvider.CreateSharedSecretTokenProvider         (AccountDetails.Name, AccountDetails.Key);       // Create a URI for the serivce bus.     Uri serviceBusUri = ServiceBusEnvironment.CreateServiceUri         ("sb", AccountDetails.Namespace, string.Empty);       // Create the MessagingFactory     MessagingFactory factory = MessagingFactory.Create(serviceBusUri, credentials);       // Use the MessagingFactory to create a queue client     QueueClient queueClient = factory.CreateQueueClient(AccountDetails.QueueName);       // Open the input file.     FileStream fileStream = new FileStream(AccountDetails.TestFile, FileMode.Open);       // Create a BrokeredMessage for the file.     BrokeredMessage largeMessage = new BrokeredMessage(fileStream, true);       Console.WriteLine("Sending: " + AccountDetails.TestFile);     Console.WriteLine("Message body size: " + largeMessage.Size);     Console.WriteLine();         // Send the message with a LargeMessageSender     LargeMessageSender sender = new LargeMessageSender(queueClient);     sender.Send(largeMessage);       // Close the messaging facory.     factory.Close();  } The implementation of the main method of the receiving application is shown below. static void Main(string[] args) {       // Create a token provider with the relevant credentials.     TokenProvider credentials =         TokenProvider.CreateSharedSecretTokenProvider         (AccountDetails.Name, AccountDetails.Key);       // Create a URI for the serivce bus.     Uri serviceBusUri = ServiceBusEnvironment.CreateServiceUri         ("sb", AccountDetails.Namespace, string.Empty);       // Create the MessagingFactory     MessagingFactory factory = MessagingFactory.Create(serviceBusUri, credentials);       // Use the MessagingFactory to create a queue client     QueueClient queueClient = factory.CreateQueueClient(AccountDetails.QueueName);       // Create a LargeMessageReceiver and receive the message.     LargeMessageReceiver receiver = new LargeMessageReceiver(queueClient);     BrokeredMessage largeMessage = receiver.Receive();       Console.WriteLine("Received message");     Console.WriteLine("Message body size: " + largeMessage.Size);       string testFile = AccountDetails.TestFile.Replace(@"\In\", @"\Out\");     Console.WriteLine("Saving file: " + testFile);       // Save the message body as a file.     Stream largeMessageStream = largeMessage.GetBody<Stream>();     largeMessageStream.Seek(0, SeekOrigin.Begin);     FileStream fileOut = new FileStream(testFile, FileMode.Create);     largeMessageStream.CopyTo(fileOut);     fileOut.Close();       Console.WriteLine("Done!"); } In order to test the application, the sending application is executed, which will use the LargeMessageSender class to split the message and place it on the queue. The output of the sender console is shown below. The console shows that the body size of the large message was 9,929,365 bytes, and the message was sent as a sequence of 51 sub messages. When the receiving application is executed the results are shown below. The console application shows that the aggregator has received the 51 messages from the message sequence that was creating in the sending application. The messages have been aggregated to form a massage with a body of 9,929,365 bytes, which is the same as the original large message. The message body is then saved as a file. Improvements to the Implementation The splitter and aggregator patterns in this implementation were created in order to show the usage of the patterns in a demo, which they do quite well. When implementing these patterns in a real-world scenario there are a number of improvements that could be made to the design. Copying Message Header Properties When sending a large message using these classes, it would be great if the message header properties in the message that was received were copied from the message that was sent. The sending application may well add information to the message context that will be required in the receiving application. When the sub messages are created in the splitter, the header properties in the first message could be set to the values in the original large message. The aggregator could then used the values from this first sub message to set the properties in the message header of the large message during the aggregation process. Using Asynchronous Methods The current implementation uses the synchronous send and receive methods of the QueueClient class. It would be much more performant to use the asynchronous methods, however doing so may well affect the sequence in which the sub messages are enqueued, which would require the implementation of a resequencer in the aggregator to restore the correct message sequence. Handling Exceptions In order to keep the code readable no exception handling was added to the implementations. In a real-world scenario exceptions should be handled accordingly.

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  • 64-bit Archives Needed

    - by user9154181
    A little over a year ago, we received a question from someone who was trying to build software on Solaris. He was getting errors from the ar command when creating an archive. At that time, the ar command on Solaris was a 32-bit command. There was more than 2GB of data, and the ar command was hitting the file size limit for a 32-bit process that doesn't use the largefile APIs. Even in 2011, 2GB is a very large amount of code, so we had not heard this one before. Most of our toolchain was extended to handle 64-bit sized data back in the 1990's, but archives were not changed, presumably because there was no perceived need for it. Since then of course, programs have continued to get larger, and in 2010, the time had finally come to investigate the issue and find a way to provide for larger archives. As part of that process, I had to do a deep dive into the archive format, and also do some Unix archeology. I'm going to record what I learned here, to document what Solaris does, and in the hope that it might help someone else trying to solve the same problem for their platform. Archive Format Details Archives are hardly cutting edge technology. They are still used of course, but their basic form hasn't changed in decades. Other than to fix a bug, which is rare, we don't tend to touch that code much. The archive file format is described in /usr/include/ar.h, and I won't repeat the details here. Instead, here is a rough overview of the archive file format, implemented by System V Release 4 (SVR4) Unix systems such as Solaris: Every archive starts with a "magic number". This is a sequence of 8 characters: "!<arch>\n". The magic number is followed by 1 or more members. A member starts with a fixed header, defined by the ar_hdr structure in/usr/include/ar.h. Immediately following the header comes the data for the member. Members must be padded at the end with newline characters so that they have even length. The requirement to pad members to an even length is a dead giveaway as to the age of the archive format. It tells you that this format dates from the 1970's, and more specifically from the era of 16-bit systems such as the PDP-11 that Unix was originally developed on. A 32-bit system would have required 4 bytes, and 64-bit systems such as we use today would probably have required 8 bytes. 2 byte alignment is a poor choice for ELF object archive members. 32-bit objects require 4 byte alignment, and 64-bit objects require 64-bit alignment. The link-editor uses mmap() to process archives, and if the members have the wrong alignment, we have to slide (copy) them to the correct alignment before we can access the ELF data structures inside. The archive format requires 2 byte padding, but it doesn't prohibit more. The Solaris ar command takes advantage of this, and pads ELF object members to 8 byte boundaries. Anything else is padded to 2 as required by the format. The archive header (ar_hdr) represents all numeric values using an ASCII text representation rather than as binary integers. This means that an archive that contains only text members can be viewed using tools such as cat, more, or a text editor. The original designers of this format clearly thought that archives would be used for many file types, and not just for objects. Things didn't turn out that way of course — nearly all archives contain relocatable objects for a single operating system and machine, and are used primarily as input to the link-editor (ld). Archives can have special members that are created by the ar command rather than being supplied by the user. These special members are all distinguished by having a name that starts with the slash (/) character. This is an unambiguous marker that says that the user could not have supplied it. The reason for this is that regular archive members are given the plain name of the file that was inserted to create them, and any path components are stripped off. Slash is the delimiter character used by Unix to separate path components, and as such cannot occur within a plain file name. The ar command hides the special members from you when you list the contents of an archive, so most users don't know that they exist. There are only two possible special members: A symbol table that maps ELF symbols to the object archive member that provides it, and a string table used to hold member names that exceed 15 characters. The '/' convention for tagging special members provides room for adding more such members should the need arise. As I will discuss below, we took advantage of this fact to add an alternate 64-bit symbol table special member which is used in archives that are larger than 4GB. When an archive contains ELF object members, the ar command builds a special archive member known as the symbol table that maps all ELF symbols in the object to the archive member that provides it. The link-editor uses this symbol table to determine which symbols are provided by the objects in that archive. If an archive has a symbol table, it will always be the first member in the archive, immediately following the magic number. Unlike member headers, symbol tables do use binary integers to represent offsets. These integers are always stored in big-endian format, even on a little endian host such as x86. The archive header (ar_hdr) provides 15 characters for representing the member name. If any member has a name that is longer than this, then the real name is written into a special archive member called the string table, and the member's name field instead contains a slash (/) character followed by a decimal representation of the offset of the real name within the string table. The string table is required to precede all normal archive members, so it will be the second member if the archive contains a symbol table, and the first member otherwise. The archive format is not designed to make finding a given member easy. Such operations move through the archive from front to back examining each member in turn, and run in O(n) time. This would be bad if archives were commonly used in that manner, but in general, they are not. Typically, the ar command is used to build an new archive from scratch, inserting all the objects in one operation, and then the link-editor accesses the members in the archive in constant time by using the offsets provided by the symbol table. Both of these operations are reasonably efficient. However, listing the contents of a large archive with the ar command can be rather slow. Factors That Limit Solaris Archive Size As is often the case, there was more than one limiting factor preventing Solaris archives from growing beyond the 32-bit limits of 2GB (32-bit signed) and 4GB (32-bit unsigned). These limits are listed in the order they are hit as archive size grows, so the earlier ones mask those that follow. The original Solaris archive file format can handle sizes up to 4GB without issue. However, the ar command was delivered as a 32-bit executable that did not use the largefile APIs. As such, the ar command itself could not create a file larger than 2GB. One can solve this by building ar with the largefile APIs which would allow it to reach 4GB, but a simpler and better answer is to deliver a 64-bit ar, which has the ability to scale well past 4GB. Symbol table offsets are stored as 32-bit big-endian binary integers, which limits the maximum archive size to 4GB. To get around this limit requires a different symbol table format, or an extension mechanism to the current one, similar in nature to the way member names longer than 15 characters are handled in member headers. The size field in the archive member header (ar_hdr) is an ASCII string capable of representing a 32-bit unsigned value. This places a 4GB size limit on the size of any individual member in an archive. In considering format extensions to get past these limits, it is important to remember that very few archives will require the ability to scale past 4GB for many years. The old format, while no beauty, continues to be sufficient for its purpose. This argues for a backward compatible fix that allows newer versions of Solaris to produce archives that are compatible with older versions of the system unless the size of the archive exceeds 4GB. Archive Format Differences Among Unix Variants While considering how to extend Solaris archives to scale to 64-bits, I wanted to know how similar archives from other Unix systems are to those produced by Solaris, and whether they had already solved the 64-bit issue. I've successfully moved archives between different Unix systems before with good luck, so I knew that there was some commonality. If it turned out that there was already a viable defacto standard for 64-bit archives, it would obviously be better to adopt that rather than invent something new. The archive file format is not formally standardized. However, the ar command and archive format were part of the original Unix from Bell Labs. Other systems started with that format, extending it in various often incompatible ways, but usually with the same common shared core. Most of these systems use the same magic number to identify their archives, despite the fact that their archives are not always fully compatible with each other. It is often true that archives can be copied between different Unix variants, and if the member names are short enough, the ar command from one system can often read archives produced on another. In practice, it is rare to find an archive containing anything other than objects for a single operating system and machine type. Such an archive is only of use on the type of system that created it, and is only used on that system. This is probably why cross platform compatibility of archives between Unix variants has never been an issue. Otherwise, the use of the same magic number in archives with incompatible formats would be a problem. I was able to find information for a number of Unix variants, described below. These can be divided roughly into three tribes, SVR4 Unix, BSD Unix, and IBM AIX. Solaris is a SVR4 Unix, and its archives are completely compatible with those from the other members of that group (GNU/Linux, HP-UX, and SGI IRIX). AIX AIX is an exception to rule that Unix archive formats are all based on the original Bell labs Unix format. It appears that AIX supports 2 formats (small and big), both of which differ in fundamental ways from other Unix systems: These formats use a different magic number than the standard one used by Solaris and other Unix variants. They include support for removing archive members from a file without reallocating the file, marking dead areas as unused, and reusing them when new archive items are inserted. They have a special table of contents member (File Member Header) which lets you find out everything that's in the archive without having to actually traverse the entire file. Their symbol table members are quite similar to those from other systems though. Their member headers are doubly linked, containing offsets to both the previous and next members. Of the Unix systems described here, AIX has the only format I saw that will have reasonable insert/delete performance for really large archives. Everyone else has O(n) performance, and are going to be slow to use with large archives. BSD BSD has gone through 4 versions of archive format, which are described in their manpage. They use the same member header as SVR4, but their symbol table format is different, and their scheme for long member names puts the name directly after the member header rather than into a string table. GNU/Linux The GNU toolchain uses the SVR4 format, and is compatible with Solaris. HP-UX HP-UX seems to follow the SVR4 model, and is compatible with Solaris. IRIX IRIX has 32 and 64-bit archives. The 32-bit format is the standard SVR4 format, and is compatible with Solaris. The 64-bit format is the same, except that the symbol table uses 64-bit integers. IRIX assumes that an archive contains objects of a single ELFCLASS/MACHINE, and any archive containing ELFCLASS64 objects receives a 64-bit symbol table. Although they only use it for 64-bit objects, nothing in the archive format limits it to ELFCLASS64. It would be perfectly valid to produce a 64-bit symbol table in an archive containing 32-bit objects, text files, or anything else. Tru64 Unix (Digital/Compaq/HP) Tru64 Unix uses a format much like ours, but their symbol table is a hash table, making specific symbol lookup much faster. The Solaris link-editor uses archives by examining the entire symbol table looking for unsatisfied symbols for the link, and not by looking up individual symbols, so there would be no benefit to Solaris from such a hash table. The Tru64 ld must use a different approach in which the hash table pays off for them. Widening the existing SVR4 archive symbol tables rather than inventing something new is the simplest path forward. There is ample precedent for this approach in the ELF world. When ELF was extended to support 64-bit objects, the approach was largely to take the existing data structures, and define 64-bit versions of them. We called the old set ELF32, and the new set ELF64. My guess is that there was no need to widen the archive format at that time, but had there been, it seems obvious that this is how it would have been done. The Implementation of 64-bit Solaris Archives As mentioned earlier, there was no desire to improve the fundamental nature of archives. They have always had O(n) insert/delete behavior, and for the most part it hasn't mattered. AIX made efforts to improve this, but those efforts did not find widespread adoption. For the purposes of link-editing, which is essentially the only thing that archives are used for, the existing format is adequate, and issues of backward compatibility trump the desire to do something technically better. Widening the existing symbol table format to 64-bits is therefore the obvious way to proceed. For Solaris 11, I implemented that, and I also updated the ar command so that a 64-bit version is run by default. This eliminates the 2 most significant limits to archive size, leaving only the limit on an individual archive member. We only generate a 64-bit symbol table if the archive exceeds 4GB, or when the new -S option to the ar command is used. This maximizes backward compatibility, as an archive produced by Solaris 11 is highly likely to be less than 4GB in size, and will therefore employ the same format understood by older versions of the system. The main reason for the existence of the -S option is to allow us to test the 64-bit format without having to construct huge archives to do so. I don't believe it will find much use outside of that. Other than the new ability to create and use extremely large archives, this change is largely invisible to the end user. When reading an archive, the ar command will transparently accept either form of symbol table. Similarly, the ELF library (libelf) has been updated to understand either format. Users of libelf (such as the link-editor ld) do not need to be modified to use the new format, because these changes are encapsulated behind the existing functions provided by libelf. As mentioned above, this work did not lift the limit on the maximum size of an individual archive member. That limit remains fixed at 4GB for now. This is not because we think objects will never get that large, for the history of computing says otherwise. Rather, this is based on an estimation that single relocatable objects of that size will not appear for a decade or two. A lot can change in that time, and it is better not to overengineer things by writing code that will sit and rot for years without being used. It is not too soon however to have a plan for that eventuality. When the time comes when this limit needs to be lifted, I believe that there is a simple solution that is consistent with the existing format. The archive member header size field is an ASCII string, like the name, and as such, the overflow scheme used for long names can also be used to handle the size. The size string would be placed into the archive string table, and its offset in the string table would then be written into the archive header size field using the same format "/ddd" used for overflowed names.

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  • Optimizing transition/movement smoothness for a 2D flash game.

    - by Tom
    Update 6: Fenomenas suggested me to re-create everything as simple as possible. I had my doubts that this would make any difference as the algorithm remains the same, and performance did not seem to be the issue. Anyway, it was the only suggestion I got so here it is: 30 FPS: http://www.feedpostal.com/test/simple/30/SimpleMovement.html 40 FPS: http://www.feedpostal.com/test/simple/40/SimpleMovement.html 60 FPS: http://www.feedpostal.com/test/simple/60/SimpleMovement.html 100 FPS: http://www.feedpostal.com/test/simple/100/SimpleMovement.html The code: package { import flash.display.Sprite; import flash.events.Event; import flash.events.KeyboardEvent; import flash.utils.getTimer; [SWF(width="800", height="600", frameRate="40", backgroundColor="#000000")] public class SimpleMovement extends Sprite { private static const TURNING_SPEED:uint = 180; private static const MOVEMENT_SPEED:uint = 400; private static const RADIAN_DIVIDE:Number = Math.PI/180; private var playerObject:Sprite; private var shipContainer:Sprite; private var moving:Boolean = false; private var turningMode:uint = 0; private var movementTimestamp:Number = getTimer(); private var turningTimestamp:Number = movementTimestamp; public function SimpleMovement() { //step 1: create player object playerObject = new Sprite(); playerObject.graphics.lineStyle(1, 0x000000); playerObject.graphics.beginFill(0x6D7B8D); playerObject.graphics.drawRect(0, 0, 25, 50); //make it rotate around the center playerObject.x = 0 - playerObject.width / 2; playerObject.y = 0 - playerObject.height / 2; shipContainer = new Sprite(); shipContainer.addChild(playerObject); shipContainer.x = 100; shipContainer.y = 100; shipContainer.rotation = 180; addChild(shipContainer); //step 2: install keyboard hook when stage is ready addEventListener(Event.ADDED_TO_STAGE, stageReady, false, 0, true); //step 3: install rendering update poll addEventListener(Event.ENTER_FRAME, updatePoller, false, 0, true); } private function updatePoller(event:Event):void { var newTime:Number = getTimer(); //turning if (turningMode != 0) { var turningDeltaTime:Number = newTime - turningTimestamp; turningTimestamp = newTime; var rotation:Number = TURNING_SPEED * turningDeltaTime / 1000; if (turningMode == 1) shipContainer.rotation -= rotation; else shipContainer.rotation += rotation; } //movement if (moving) { var movementDeltaTime:Number = newTime - movementTimestamp; movementTimestamp = newTime; var distance:Number = MOVEMENT_SPEED * movementDeltaTime / 1000; var rAngle:Number = shipContainer.rotation * RADIAN_DIVIDE; //convert degrees to radian shipContainer.x += distance * Math.sin(rAngle); shipContainer.y -= distance * Math.cos(rAngle); } } private function stageReady(event:Event):void { //install keyboard hook stage.addEventListener(KeyboardEvent.KEY_DOWN, keyDown, false, 0, true); stage.addEventListener(KeyboardEvent.KEY_UP, keyUp, false, 0, true); } private final function keyDown(event:KeyboardEvent):void { if ((event.keyCode == 87) && (!moving)) //87 = W { movementTimestamp = getTimer(); moving = true; } if ((event.keyCode == 65) && (turningMode != 1)) //65 = A { turningTimestamp = getTimer(); turningMode = 1; } else if ((event.keyCode == 68) && (turningMode != 2)) //68 = D { turningTimestamp = getTimer(); turningMode = 2; } } private final function keyUp(event:KeyboardEvent):void { if ((event.keyCode == 87) && (moving)) moving = false; //87 = W if (((event.keyCode == 65) || (event.keyCode == 68)) && (turningMode != 0)) turningMode = 0; //65 = A, 68 = D } } } The results were as I expected. Absolutely no improvement. I really hope that someone has another suggestion as this thing needs fixing. Also, I doubt it's my system as I have a pretty good one (8GB RAM, Q9550 QuadCore intel, ATI Radeon 4870 512MB). Also, everyone else I asked so far had the same issue with my client. Update 5: another example of a smooth flash game just to demonstrate that my movement definitely is different! See http://www.spel.nl/game/bumpercraft.html Update 4: I traced the time before rendering (EVENT.RENDER) and right after rendering (EVENT.ENTER_FRAME), the results: rendering took: 14 ms rendering took: 14 ms rendering took: 12 ms rendering took: 16 ms rendering took: 12 ms rendering took: 14 ms rendering took: 14 ms rendering took: 12 ms rendering took: 16 ms rendering took: 12 ms rendering took: 14 ms rendering took: 14 ms rendering took: 12 ms rendering took: 16 ms rendering took: 12 ms rendering took: 14 ms rendering took: 12 ms rendering took: 14 ms rendering took: 16 ms rendering took: 12 ms rendering took: 14 ms rendering took: 12 ms rendering took: 14 ms rendering took: 16 ms rendering took: 12 ms rendering took: 14 ms rendering took: 12 ms rendering took: 14 ms rendering took: 16 ms rendering took: 12 ms rendering took: 14 ms rendering took: 12 ms rendering took: 14 ms rendering took: 16 ms rendering took: 12 ms rendering took: 14 ms rendering took: 12 ms rendering took: 14 ms rendering took: 16 ms rendering took: 12 ms rendering took: 14 ms rendering took: 12 ms rendering took: 14 ms rendering took: 16 ms rendering took: 12 ms rendering took: 14 ms rendering took: 12 ms rendering took: 14 ms rendering took: 16 ms rendering took: 12 ms rendering took: 14 ms rendering took: 12 ms rendering took: 14 ms rendering took: 16 ms rendering took: 12 ms rendering took: 14 ms rendering took: 12 ms rendering took: 14 ms rendering took: 16 ms rendering took: 12 ms rendering took: 14 ms rendering took: 12 ms rendering took: 14 ms rendering took: 16 ms rendering took: 12 ms rendering took: 14 ms rendering took: 12 ms rendering took: 14 ms rendering took: 16 ms rendering took: 12 ms rendering took: 14 ms rendering took: 12 ms rendering took: 14 ms rendering took: 16 ms rendering took: 12 ms rendering took: 14 ms rendering took: 12 ms rendering took: 14 ms rendering took: 14 ms rendering took: 14 ms rendering took: 14 ms rendering took: 12 ms rendering took: 14 ms rendering took: 16 ms rendering took: 12 ms rendering took: 24 ms rendering took: 18 ms rendering took: 16 ms rendering took: 12 ms rendering took: 14 ms rendering took: 12 ms rendering took: 14 ms rendering took: 16 ms rendering took: 12 ms rendering took: 14 ms rendering took: 12 ms rendering took: 14 ms rendering took: 16 ms rendering took: 12 ms rendering took: 14 ms rendering took: 12 ms rendering took: 14 ms rendering took: 16 ms rendering took: 12 ms rendering took: 14 ms rendering took: 12 ms rendering took: 14 ms rendering took: 16 ms rendering took: 12 ms rendering took: 14 ms rendering took: 12 ms rendering took: 14 ms rendering took: 16 ms rendering took: 12 ms rendering took: 14 ms rendering took: 12 ms rendering took: 14 ms rendering took: 16 ms rendering took: 12 ms rendering took: 14 ms rendering took: 12 ms rendering took: 14 ms rendering took: 16 ms rendering took: 12 ms rendering took: 14 ms rendering took: 12 ms rendering took: 14 ms rendering took: 16 ms rendering took: 12 ms rendering took: 14 ms rendering took: 12 ms rendering took: 14 ms rendering took: 16 ms rendering took: 12 ms rendering took: 14 ms rendering took: 12 ms rendering took: 14 ms rendering took: 16 ms rendering took: 12 ms rendering took: 14 ms rendering took: 12 ms rendering took: 14 ms rendering took: 16 ms rendering took: 12 ms rendering took: 14 ms rendering took: 12 ms rendering took: 14 ms rendering took: 16 ms rendering took: 12 ms rendering took: 14 ms rendering took: 12 ms rendering took: 14 ms rendering took: 16 ms rendering took: 12 ms rendering took: 14 ms rendering took: 12 ms rendering took: 14 ms rendering took: 16 ms rendering took: 12 ms rendering took: 14 ms rendering took: 12 ms rendering took: 14 ms rendering took: 16 ms rendering took: 12 ms rendering took: 14 ms rendering took: 12 ms rendering took: 14 ms rendering took: 16 ms rendering took: 12 ms rendering took: 232 ms rendering took: 14 ms rendering took: 12 ms rendering took: 14 ms rendering took: 16 ms rendering took: 12 ms rendering took: 14 ms rendering took: 12 ms rendering took: 14 ms rendering took: 16 ms rendering took: 12 ms rendering took: 14 ms rendering took: 12 ms rendering took: 14 ms rendering took: 16 ms rendering took: 12 ms rendering took: 14 ms rendering took: 12 ms The range is 12-16 ms. During these differences, the shocking/warping/flickering movement was already going on. There is also 1 peak of 232ms, at this time there was a relatively big warp. This is however not the biggest problme, the biggest problem are the continuous small warps during normal movement. Does this give anyone a clue? Update 3: After testing, I know that the following factors are not causing my problem: Bitmap's quality - changed with photoshop to an uglier 8 colours optimized graphic, no improvement at all. Constant rotation of image while turning - disabled it, no improvement at all Browser rendering - tried to use the flash player standalone, no improvement at all I am 100% convinced that the problem lies in either my code or in my algorithm. Please, help me out. It has been almost two weeks (1 week that I asked this question on SO) now and I still have to get my golden answer. Update 1: see bottom for full flex project source and a live demo demonstrating my problem. I'm working on a 2d flash game. Player ships are created as an object: ships[id] = new GameShip(); When movement and rotation information is available, this is being directed to the corresponding ship: ships[id].setMovementMode(1); //move forward Now, within this GameShip object movement works using the "Event.ENTER_FRAME" event: addEventListener(Event.ENTER_FRAME, movementHandler); The following function is then being run: private final function movementHandler(event:Event):void { var newTimeStamp:uint = UtilLib.getTimeStamp(); //set current timeStamp var distance:Number = (newTimeStamp - movementTimeStamp) / 1000 * movementSpeed; //speed = x pixels forward every 1 second movementTimeStamp = newTimeStamp; //update old timeStamp var diagonalChange:Array = getDiagonalChange(movementAngle, distance); //the diagonal position update based on angle and distance charX += diagonalChange[0]; charY += diagonalChange[1]; if (shipContainer) { //when the container is ready to be worked with shipContainer.x = charX; shipContainer.y = charY; } } private final function getDiagonalChange(angle:Number, distance:Number):Array { var rAngle:Number = angle * Math.PI/180; //convert degrees to radian return [Math.sin(rAngle) * distance, (Math.cos(rAngle) * distance) * -1]; } When the object is no longer moving, the event listener will be removed. The same method is being used for rotation. Everything works almost perfect. I've set the project's target FPS to 100 and created a FPS counter. According to the FPS counter, the average FPS in firefox is around 100, while the top is 1000 and the bottom is 22. I think that the bottom and top FPSs are only happening during the initialization of the client (startup). The problem is that the ship appears to be almost perfectly smooth, while it should be just that without the "almost" part. It's almost as if the ship is "flickering" very very fast, you can't actually see it but it's hard to focus on the object while it's moving with your eyes. Also, every now and then, there seems to be a bit of a framerate spike, as if the client is skipping a couple of frames, you then see it quickly warp. It is very difficult to explain what the real problem is, but in general it's that the movement is not perfectly smooth. So, do you have any suggestions on how to make the movement or transition of objects perfectly smooth? Update 1: I re-created the client to demonstrate my problem. Please check it out. The client: http://feedpostal.com/test/MovementTest.html The Actionscript Project (full source): http://feedpostal.com/test/MovementTest.rar An example of a smooth flash game (not created by me): http://www.gamesforwork.com/games/swf/Mission%20Racing_august_10th_2009.swf It took me a pretty long time to recreate this client side version, I hope this will help with solving the problem. Please note: yes, it is actually pretty smooth. But it is definitely not smooth enough.

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  • Accurate least-squares fit algorithm needed

    - by ggkmath
    I've experimented with the two ways of implementing a least-squares fit (LSF) algorithm shown here. The first code is simply the textbook approach, as described by Wolfram's page on LSF. The second code re-arranges the equation to minimize machine errors. Both codes produce similar results for my data. I compared these results with Matlab's p=polyfit(x,y,1) function, using correlation coefficients to measure the "goodness" of fit and compare each of the 3 routines. I observed that while all 3 methods produced good results, at least for my data, Matlab's routine had the best fit (the other 2 routines had similar results to each other). Matlab's p=polyfit(x,y,1) function uses a Vandermonde matrix, V (n x 2 matrix) and QR factorization to solve the least-squares problem. In Matlab code, it looks like: V = [x1,1; x2,1; x3,1; ... xn,1] % this line is pseudo-code [Q,R] = qr(V,0); p = R\(Q'*y); % performs same as p = V\y I'm not a mathematician, so I don't understand why it would be more accurate. Although the difference is slight, in my case I need to obtain the slope from the LSF and multiply it by a large number, so any improvement in accuracy shows up in my results. For reasons I can't get into, I cannot use Matlab's routine in my work. So, I'm wondering if anyone has a more accurate equation-based approach recommendation I could use that is an improvement over the above two approaches, in terms of rounding errors/machine accuracy/etc. Any comments appreciated! thanks in advance.

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  • Flash video slooow in AIR 2 HTMLLoader component

    - by shane
    I am working on a full screen kiosk application in Flex 4/Air 2 using Flash Builder 4. We have a company training website which staff can access via the kiosk, and the main content is interactive flash training videos. Our target machines are by no means 'beefy', they are Atom n270s @ 1.6Ghz with 1Gb RAM. As it stands the videos are all but unusable when used from within the Air application, the application becomes completely unresponsive (100% cpu usage, click events take approx 5-10 seconds to register). So far I have tried: increasing the default frame rate from 24fps to 60. No improvement. nativeWindow.stage.frameRate = 60; running the videos in a stripped down version of my app, just a full screen HTMLLoader component pointed at the training website. No better than before. disabled hyper threading. The Atom CPU is split into two virtual cores, and the AIR app was only able to use one thread so maxed out at 50% CPU usage. Since the kiosk will only run the AIR app I am happy to loose hyper threading to increase the performance of the Air app. Marginal Improvement. The same website with the same videos is responsive if viewed in ie7 on the same machine, although Internet Explorer takes advantage of the CPU’s hyper threading. The flash videos are built with Adobe Captivate and from what I understand employee JavaScript to relay results back to the server. I will add more information about the video content asap as the training guru is back in the office later this week.

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  • Performance degrades for more than 2 threads on Xeon X5355

    - by zoolii
    Hi All, I am writing an application using boost threads and using boost barriers to synchronize the threads. I have two machines to test the application. Machine 1 is a core2 duo (T8300) cpu machine (windows XP professional - 4GB RAM) where I am getting following performance figures : Number of threads :1 , TPS :21 Number of threads :2 , TPS :35 (66 % improvement) further increase in number of threads decreases the TPS but that is understandable as the machine has only two cores. Machine 2 is a 2 quad core ( Xeon X5355) cpu machine (windows 2003 server with 4GB RAM) and has 8 effective cores. Number of threads :1 , TPS :21 Number of threads :2 , TPS :27 (28 % improvement) Number of threads :4 , TPS :25 Number of threads :8 , TPS :24 As you can see, performance is degrading after 2 threads (though it has 8 cores). If the program has some bottle neck , then for 2 thread also it should have degraded. Any idea? , Explanations ? , Does the OS has some role in performance ? - It seems like the Core2duo (2.4GHz) scales better than Xeon X5355 (2.66GHz) though it has better clock speed. Thank you -Zoolii

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  • Help with Assembly/SSE Multiplication

    - by Brett
    I've been trying to figure out how to gain some improvement in my code at a very crucial couple lines: float x = a*b; float y = c*d; float z = e*f; float w = g*h; all a, b, c... are floats. I decided to look into using SSE, but can't seem to find any improvement, in fact it turns out to be twice as slow. My SSE code is: Vector4 abcd, efgh, result; abcd = [float a, float b, float c, float d]; efgh = [float e, float f, float g, float h]; _asm { movups xmm1, abcd movups xmm2, efgh mulps xmm1, xmm2 movups result, xmm1 } I also attempted using standard inline assembly, but it doesn't appear that I can pack the register with the four floating points like I can with SSE. Any comments, or help would be greatly appreciated, I mainly need to understand why my calculations using SSE are slower than the serial C++ code? I'm compiling in Visual Studio 2005, on a Windows XP, using a Pentium 4 with HT if that provides any additional information to assit. Thanks in advance!

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  • Does fast typing influence fast programming? [closed]

    - by Lukasz Lew
    Many young programmers think that their bottleneck is typing speed. After some experience one realizes that it is not the case, you have to think much more than type. At some point my room-mate forced me to turn of the light (he sleeps during the night). I had to learn to touch type and I experienced an actual improvement in programming skill. The most surprising was that the improvement not due to sheer typing speed, but to a change in mindset. I'm less afraid now to try new things and refactor them later if they work well. It's like having a new tool in the bag. Have anyone of you had similar experience? Now I trained a touch typing a little with KTouch. I find auto-generate lessons the best. I can use this program to create new lessons out of text files but it's only verbatim training, not auto-generated based on a language model. Do you know any touch typing program that allows creation of custom, but randomized lessons?

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  • Big 0 theta notation

    - by niggersak
    Can some pls help with the solution Use big-O notation to classify the traditional grade school algorithms for addition and multiplication. That is, if asked to add two numbers each having N digits, how many individual additions must be performed? If asked to multiply two N-digit numbers, how many individual multiplications are required? Suppose f is a function that returns the result of reversing the string of symbols given as its input, and g is a function that returns the concatenation of the two strings given as its input. If x is the string hrwa, what is returned by g(f(x),x)? Explain your answer - don't just provide the result!

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  • Log4j Grouping application logs

    - by mhanda
    Hi, I am trying to group logs of multiple related applications to a single log file. For example I have 3 applications A1.esb, A2.esb, A3.esb. I want all the logs from these 3 applications get logged to a single log file called A.log. Similarly, I want B.log for B1.esb, B2.esb and B3.esb. I am using log4j in JBoss application server. I have tried to use TCLFilter but I only succeeded in getting individual applications logging to individual log files. As in, A1.esb logging to A1.log, A2.esb logging to A2.log and so on. But I couldn't figure out a way of grouping these loggings.

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  • How to get image to pulse with opacity with JQuery

    - by Alex
    I am trying to get an image to change opacity smoothly over a duration of time. Here's the code I have for it. <script type="text/javascript"> pulsem(elementid){ var element = document.getElementById(elementid) jquery(element).pulse({opacity: [0,1]}, { duration: 100, // duration of EACH individual animation times: 3, // Will go three times through the pulse array [0,1] easing: 'linear', // easing function for each individual animation complete: function() { alert("I'm done pulsing!"); } }) </script> <a href="city.htm"><img src="waterloo.png" onmouseover="javascript:pulsem("waterloo")" border="0" class="env" id="waterloo"/></a> Also, is there a way for this to happen automatically without the need of a mouseover? Thanks.

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  • Database Design for multiple users site

    - by jl
    Hi, I am required to work on a php project that requires the database to cater to multiple users. Generally, the idea is similar to what they have for carbonmade or basecamp, or even wordpress mu. They cater to multiple users, whom are also owners of their accounts. And if they were to cancel/terminate their account, anything on the pages/database would be removed. I am not quite sure how should I design the database? Should it be: separate tables for individual user account separate databases for individual user account or otherwise? Kindly advise me for the best approach to this issue. Thank you very much.

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