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  • Programação paralela no .NET Framework 4 – Parte II

    - by anobre
    Olá pessoal, tudo bem? Este post é uma continuação da série iniciada neste outro post, sobre programação paralela. Meu objetivo hoje é apresentar o PLINQ, algo que poderá ser utilizado imediatamente nos projetos de vocês. Parallel LINQ (PLINQ) PLINQ nada mais é que uma implementação de programação paralela ao nosso famoso LINQ, através de métodos de extensão. O LINQ foi lançado com a versão 3.0 na plataforma .NET, apresentando uma maneira muito mais fácil e segura de manipular coleções IEnumerable ou IEnumerable<T>. O que veremos hoje é a “alteração” do LINQ to Objects, que é direcionado a coleções de objetos em memória. A principal diferença entre o LINQ to Objects “normal” e o paralelo é que na segunda opção o processamento é realizado tentando utilizar todos os recursos disponíveis para tal, obtendo uma melhora significante de performance. CUIDADO: Nem todas as operações ficam mais rápidas utilizando recursos de paralelismo. Não deixe de ler a seção “Performance” abaixo. ParallelEnumerable Tudo que a gente precisa para este post está organizado na classe ParallelEnumerable. Esta classe contém os métodos que iremos utilizar neste post, e muito mais: AsParallel AsSequential AsOrdered AsUnordered WithCancellation WithDegreeOfParallelism WithMergeOptions WithExecutionMode ForAll … O exemplo mais básico de como executar um código PLINQ é utilizando o métodos AsParallel, como o exemplo: var source = Enumerable.Range(1, 10000); var evenNums = from num in source.AsParallel() where Compute(num) > 0 select num; Algo tão interessante quanto esta facilidade é que o PLINQ não executa sempre de forma paralela. Dependendo da situação e da análise de alguns itens no cenário de execução, talvez seja mais adequado executar o código de forma sequencial – e nativamente o próprio PLINQ faz esta escolha.  É possível forçar a execução para sempre utilizar o paralelismo, caso seja necessário. Utilize o método WithExecutionMode no seu código PLINQ. Um teste muito simples onde podemos visualizar a diferença é demonstrado abaixo: static void Main(string[] args) { IEnumerable<int> numbers = Enumerable.Range(1, 1000); IEnumerable<int> results = from n in numbers.AsParallel() where IsDivisibleByFive(n) select n; Stopwatch sw = Stopwatch.StartNew(); IList<int> resultsList = results.ToList(); Console.WriteLine("{0} itens", resultsList.Count()); sw.Stop(); Console.WriteLine("Tempo de execução: {0} ms", sw.ElapsedMilliseconds); Console.WriteLine("Fim..."); Console.ReadKey(true); } static bool IsDivisibleByFive(int i) { Thread.SpinWait(2000000); return i % 5 == 0; }   Basta remover o AsParallel da instrução LINQ que você terá uma noção prática da diferença de performance. 1. Instrução utilizando AsParallel   2. Instrução sem utilizar paralelismo Performance Apesar de todos os benefícios, não podemos utilizar PLINQ sem conhecer todos os seus detalhes. Lembre-se de fazer as perguntas básicas: Eu tenho trabalho suficiente que justifique utilizar paralelismo? Mesmo com o overhead do PLINQ, vamos ter algum benefício? Por este motivo, visite este link e conheça todos os aspectos, antes de utilizar os recursos disponíveis. Conclusão Utilizar recursos de paralelismo é ótimo, aumenta a performance, utiliza o investimento realizado em hardware – tudo isso sem custo de produtividade. Porém, não podemos usufruir de qualquer tipo de tecnologia sem conhece-la a fundo antes. Portanto, faça bom uso, mas não esqueça de manter o conhecimento a frente da empolgação. Abraços.

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  • GPU Debugging with VS 11

    - by Daniel Moth
    With VS 11 Developer Preview we have invested tremendously in parallel debugging for both CPU (managed and native) and GPU debugging. I'll be doing a whole bunch of blog posts on those topics, and in this post I just wanted to get people started with GPU debugging, i.e. with debugging C++ AMP code. First I invite you to watch 6 minutes of a glimpse of the C++ AMP debugging experience though this video (ffw to minute 51:54, up until minute 59:16). Don't read the rest of this post, just go watch that video, ideally download the High Quality WMV. Summary GPU debugging essentially means debugging the lambda that you pass to the parallel_for_each call (plus any functions you call from the lambda, of course). CPU debugging means debugging all the code above and below the parallel_for_each call, i.e. all the code except the restrict(direct3d) lambda and the functions that it calls. With VS 11 you have to choose what debugger you want to use for a particular debugging session, CPU or GPU. So you can place breakpoints all over your code, then choose what debugger you want (CPU or GPU), and you'll only be able to hit breakpoints for the code type that the debugger engine understands – the remaining breakpoints will appear as unbound. If you want to hit the unbound breakpoints, you'd have to stop debugging, and start again with the other debugger. Sorry. We suck. We know. But once you are past that limitation, I think you'll find the experience truly rewarding – seriously! Switching debugger engines With the Developer Preview bits, one way to switch the debugger engine is through the project properties – see the screenshots that follow. This one is showing the CPU option selected, which is basically the default that you are all familiar with: This screenshot is showing the GPU option selected, by changing the debugger launcher (notice that this applies for both the local and remote case): You actually do not have to open the project properties just for switching the debugger engine, you can switch the selection from the toolbar in VS 11 Developer Preview too – see following screenshot (the effect is the same as if you opened the project properties and switched there) Breakpoint behavior Here are two screenshots, one showing a debugging session for CPU and the other a debugging session for GPU (notice the unbound breakpoints in each case) …and here is the GPU case (where we cannot bind the CPU breakpoints but can the GPU breakpoint, which is actually hit) Give C++ AMP debugging a try So to debug your C++ AMP code, pull down the drop down under the 'play' button to select the 'GPU C++ Direct3D Compute Debugger' menu option, then hit F5 (or the 'play' button itself). Then you can explore debugging by exploring the menus under the Debug and under the Debug->Windows menus. One way to do that exploration is through the C++ AMP debugging walkthrough on MSDN. Another way to explore the C++ AMP debugging experience, you can use the moth.cpp code file, which is what I used in my BUILD session debugger demo. Note that for my demo I was using the latest internal VS11 bits, so your experience with the Developer Preview bits won't be identical to what you saw me demonstrate, but it shouldn't be far off. Stay tuned for a lot more content on the parallel debugger in VS 11, both CPU and GPU, both managed and native. Comments about this post by Daniel Moth welcome at the original blog.

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  • SQL SERVER – Weekend Project – Experimenting with ACID Transactions, SQL Compliant, Elastically Scalable Database

    - by pinaldave
    Database technology is huge and big world. I like to explore always beyond what I know and share the learning. Weekend is the best time when I sit around download random software on my machine which I like to call as a lab machine (it is a pretty old laptop, hardly a quality as lab machine) and experiment it. There are so many free betas available for download that it’s hard to keep track and even harder to find the time to play with very many of them.  This blog is about one you shouldn’t miss if you are interested in the learning various relational databases. NuoDB just released their Beta 7.  I had already downloaded their Beta 6 and yesterday did the same for 7.   My impression is that they are onto something very very interesting.  In fact, it might be something really promising in terms of database elasticity, scale and operational cost reduction. The folks at NuoDB say they are working on the world’s first “emergent” database which they tout as a brand new transitional database that is intended to dramatically change what’s possible with OLTP.  It is SQL compliant, guarantees ACID transactions, yet scales elastically on heterogeneous and decentralized cloud-based resources. Interesting note for sure, making me explore more. Based on what I’ve seen so far, they are solving the architectural challenge that exists between elastic, cloud-based compute infrastructures designed to scale out in response to workload requirements versus the traditional relational database management system’s architecture of central control. Here’s my experience with the NuoDB Beta 6 so far: First they pretty much threw away all the features you’d associate with existing RDBMS architectures except the SQL and ACID transactions which they were smart to keep.  It looks like they have incorporated a number of the big ideas from various algorithms, systems and techniques to achieve maximum DB scalability. From a user’s perspective, the NuoDB Beta software behaves like any other traditional SQL database and seems to offer all the benefits users have come to expect from standards-based SQL solutions. One of the interesting feature is that one can run a transactional node and a storage node on my Windows laptop as well on other platforms – indeed interesting for sure. It’s quite amazing to see a database elastically scale across machine boundaries. So, one of the basic NuoDB concepts is that as you need to scale out, you can easily use more inexpensive hardware when/where you need it.  This is unlike what we have traditionally done to scale a database for an application – we replace the hardware with something more powerful (faster CPU and Disks). This is where I started to feel like NuoDB is on to something that has the potential to elastically scale on commodity hardware while reducing operational expense for a big OLTP database to a degree we’ve never seen before. NuoDB is able to fully leverage the cloud in an asynchronous and highly decentralized manner – while providing both SQL compliance and ACID transactions. Basically what NuoDB is doing is so new that it is all hard to believe until you’ve experienced it in action.  I will keep you up to date as I test the NuoDB Beta 7 but if you are developing a web-scale application or have an on-premise app you are thinking of moving to the cloud, testing this beta is worth your time. If you do try it, let me know what you think.  Before I say anything more, I am going to do more experiments and more test on this product and compare it with other existing similar products. For me it was a weekend worth spent on learning something new. I encourage you to download Beta 7 version and share your opinions here. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Documentation, SQL Download, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • Oracle Big Data Software Downloads

    - by Mike.Hallett(at)Oracle-BI&EPM
    Companies have been making business decisions for decades based on transactional data stored in relational databases. Beyond that critical data, is a potential treasure trove of less structured data: weblogs, social media, email, sensors, and photographs that can be mined for useful information. Oracle offers a broad integrated portfolio of products to help you acquire and organize these diverse data sources and analyze them alongside your existing data to find new insights and capitalize on hidden relationships. Oracle Big Data Connectors Downloads here, includes: Oracle SQL Connector for Hadoop Distributed File System Release 2.1.0 Oracle Loader for Hadoop Release 2.1.0 Oracle Data Integrator Companion 11g Oracle R Connector for Hadoop v 2.1 Oracle Big Data Documentation The Oracle Big Data solution offers an integrated portfolio of products to help you organize and analyze your diverse data sources alongside your existing data to find new insights and capitalize on hidden relationships. Oracle Big Data, Release 2.2.0 - E41604_01 zip (27.4 MB) Integrated Software and Big Data Connectors User's Guide HTML PDF Oracle Data Integrator (ODI) Application Adapter for Hadoop Apache Hadoop is designed to handle and process data that is typically from data sources that are non-relational and data volumes that are beyond what is handled by relational databases. Typical processing in Hadoop includes data validation and transformations that are programmed as MapReduce jobs. Designing and implementing a MapReduce job usually requires expert programming knowledge. However, when you use Oracle Data Integrator with the Application Adapter for Hadoop, you do not need to write MapReduce jobs. Oracle Data Integrator uses Hive and the Hive Query Language (HiveQL), a SQL-like language for implementing MapReduce jobs. Employing familiar and easy-to-use tools and pre-configured knowledge modules (KMs), the application adapter provides the following capabilities: Loading data into Hadoop from the local file system and HDFS Performing validation and transformation of data within Hadoop Loading processed data from Hadoop to an Oracle database for further processing and generating reports Oracle Database Loader for Hadoop Oracle Loader for Hadoop is an efficient and high-performance loader for fast movement of data from a Hadoop cluster into a table in an Oracle database. It pre-partitions the data if necessary and transforms it into a database-ready format. Oracle Loader for Hadoop is a Java MapReduce application that balances the data across reducers to help maximize performance. Oracle R Connector for Hadoop Oracle R Connector for Hadoop is a collection of R packages that provide: Interfaces to work with Hive tables, the Apache Hadoop compute infrastructure, the local R environment, and Oracle database tables Predictive analytic techniques, written in R or Java as Hadoop MapReduce jobs, that can be applied to data in HDFS files You install and load this package as you would any other R package. Using simple R functions, you can perform tasks such as: Access and transform HDFS data using a Hive-enabled transparency layer Use the R language for writing mappers and reducers Copy data between R memory, the local file system, HDFS, Hive, and Oracle databases Schedule R programs to execute as Hadoop MapReduce jobs and return the results to any of those locations Oracle SQL Connector for Hadoop Distributed File System Using Oracle SQL Connector for HDFS, you can use an Oracle Database to access and analyze data residing in Hadoop in these formats: Data Pump files in HDFS Delimited text files in HDFS Hive tables For other file formats, such as JSON files, you can stage the input in Hive tables before using Oracle SQL Connector for HDFS. Oracle SQL Connector for HDFS uses external tables to provide Oracle Database with read access to Hive tables, and to delimited text files and Data Pump files in HDFS. Related Documentation Cloudera's Distribution Including Apache Hadoop Library HTML Oracle R Enterprise HTML Oracle NoSQL Database HTML Recent Blog Posts Big Data Appliance vs. DIY Price Comparison Big Data: Architecture Overview Big Data: Achieve the Impossible in Real-Time Big Data: Vertical Behavioral Analytics Big Data: In-Memory MapReduce Flume and Hive for Log Analytics Building Workflows in Oozie

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  • Windows Azure Mobile Services Updates Keep Coming

    - by Clint Edmonson
    Some exciting new Windows Azure Mobile Services features were delivered to production this week. The highlights include: iPhone and iPad connectivity support via a new iOS SDK Integrated Authentication so developers can configure user authentication via Microsoft Account, Facebook, Twitter, and Google. New server-side Mobile Service script modules Access to Structured Storage, Windows Azure Blob, Table, Queues, and ServiceBus Email services through partnership with SendGrid SMS & voice services through partnership with Twilio Mobile Services hosting expanded to west coast US The iOS SDK I’m excited to share that we've announced the release of an under-development iOS client SDK for Windows Azure Mobile Services. The iOS SDK joins the Windows 8 SDK launched with Windows Azure Mobile Services as well as client SDKs released by Xamarin for MonoTouch and MonoDroid.  The native iOS SDK is for developers programming in Objective-C on the iPhone and iPad platforms. The SDK gives developers the same level of access to data storage using dynamic schematization that is available for Windows 8. Also, iOS applications can use the same authentication options available in Mobile Services. While full iOS support is still in development, the libraries are currently available on GitHub. There’s a great getting started tutorial to walk you through building a simple iOS “Todo List” app that stores data in Windows Azure.  These additional tutorials explore how to use the iOS client libraries to store data and authenticate users: Get Started with data in Mobile Services for iOS Get Started with authentication in Mobile Services for iOS What’s New in Authentication Available to both iOS and Windows 8 developers, Mobile Services has expanded its authentication options.  Developers can now use Microsoft, Facebook, Twitter, and Google authentication. Similar to using Microsoft accounts for authentication, developers must sign up and through Facebook, Twitter, or Google's developer portal in order to authenticate through them.  These tutorials walk through how to register your Mobile Service with an identity provider: How to register your app with Microsoft Account How to register your app with Facebook How to register your app with Twitter How to register your app with Google And these tutorials walk through authenticating against Mobile Services: Get started with authentication in Mobile Services for Windows Store (C#) Get started with authentication in Mobile Services for Windows Store (JavaScript) Get started with authentication in Mobile Services for iOS What’s New in Mobile Service Scripts Some great new functionality is now available in the Mobile Service script layer.  These server side scripts are triggered off of any CRUD operation on a Mobile Service's table and can already handle doing data and query validation, filtering, web requests and more.  Today, the Azure SDK module is now available to these scripts giving them access to blob storage, service bus, table storage.  Check out the new tutorials on the Windows Azure Node.js developer center to learn more about working with Blob, Tables, Queues and Service Bus using the azure module. In addition, SendGrid and Twilio are now available via modules that can be called from the scripts as well.  This gives developers the ability to send emails (SendGrid) or SMS text messages (Twilio) whenever a script is fired.  Windows Azure customers receive a special offer of 25,000 free emails per month from SendGrid and 1000 free text messages from Twilio. Expanded Data Center Availability In addition to Mobile Services being available in our US East data center, they can now be spun up in US West. The above features are all now live in production and are available to use immediately.  If you don’t already have a Windows Azure account, you can sign-up for a free trial and start using Mobile Services today. The Windows Azure Mobile Developer Center has been updated with new tutorials that cover these new features in detail. And don’t forget - Windows Azure Mobile Services are still free for your first ten applications running on shared compute instances. Stay tuned to my twitter feed for Windows Azure announcements, updates, and links: @clinted

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  • Unleash the Power of Cryptography on SPARC T4

    - by B.Koch
    by Rob Ludeman Oracle’s SPARC T4 systems are architected to deliver enhanced value for customer via the inclusion of many integrated features.  One of the best examples of this approach is demonstrated in the on-chip cryptographic support that delivers wire speed encryption capabilities without any impact to application performance.  The Evolution of SPARC Encryption SPARC T-Series systems have a long history of providing this capability, dating back to the release of the first T2000 systems that featured support for on-chip RSA encryption directly in the UltraSPARC T1 processor.  Successive generations have built on this approach by support for additional encryption ciphers that are tightly coupled with the Oracle Solaris 10 and Solaris 11 encryption framework.  While earlier versions of this technology were implemented using co-processors, the SPARC T4 was redesigned with new crypto instructions to eliminate some of the performance overhead associated with the former approach, resulting in much higher performance for encrypted workloads. The Superiority of the SPARC T4 Approach to Crypto As companies continue to engage in more and more e-commerce, the need to provide greater degrees of security for these transactions is more critical than ever before.  Traditional methods of securing data in transit by applications have a number of drawbacks that are addressed by the SPARC T4 cryptographic approach. 1. Performance degradation – cryptography is highly compute intensive and therefore, there is a significant cost when using other architectures without embedded crypto functionality.  This performance penalty impacts the entire system, slowing down performance of web servers (SSL), for example, and potentially bogging down the speed of other business applications.  The SPARC T4 processor enables customers to deliver high levels of security to internal and external customers while not incurring an impact to overall SLAs in their IT environment. 2. Added cost – one of the methods to avoid performance degradation is the addition of add-in cryptographic accelerator cards or external offload engines in other systems.  While these solutions provide a brute force mechanism to avoid the problem of slower system performance, it usually comes at an added cost.  Customers looking to encrypt datacenter traffic without the overhead and expenditure of extra hardware can rely on SPARC T4 systems to deliver the performance necessary without the need to purchase other hardware or add-on cards. 3. Higher complexity – the addition of cryptographic cards or leveraging load balancers to perform encryption tasks results in added complexity from a management standpoint.  With SPARC T4, encryption keys and the framework built into Solaris 10 and 11 means that administrators generally don’t need to spend extra cycles determining how to perform cryptographic functions.  In fact, many of the instructions are built-in and require no user intervention to be utilized.  For example, For OpenSSL on Solaris 11, SPARC T4 crypto is available directly with a new built-in OpenSSL 1.0 engine, called the "t4 engine."  For a deeper technical dive into the new instructions included in SPARC T4, consult Dan Anderson’s blog. Conclusion In summary, SPARC T4 systems offer customers much more value for applications than just increased performance. The integration of key virtualization technologies, embedded encryption, and a true Enterprise Operating System, Oracle Solaris, provides direct business benefits that supersedes the commodity approach to data center computing.   SPARC T4 removes the roadblocks to secure computing by offering integrated crypto accelerators that can save IT organizations in operating cost while delivering higher levels of performance and meeting objectives around compliance. For more on the SPARC T4 family of products, go to here.

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  • Fastest pathfinding for static node matrix

    - by Sean Martin
    I'm programming a route finding routine in VB.NET for an online game I play, and I'm searching for the fastest route finding algorithm for my map type. The game takes place in space, with thousands of solar systems connected by jump gates. The game devs have provided a DB dump containing a list of every system and the systems it can jump to. The map isn't quite a node tree, since some branches can jump to other branches - more of a matrix. What I need is a fast pathfinding algorithm. I have already implemented an A* routine and a Dijkstra's, both find the best path but are too slow for my purposes - a search that considers about 5000 nodes takes over 20 seconds to compute. A similar program on a website can do the same search in less than a second. This website claims to use D*, which I have looked into. That algorithm seems more appropriate for dynamic maps rather than one that does not change - unless I misunderstand it's premise. So is there something faster I can use for a map that is not your typical tile/polygon base? GBFS? Perhaps a DFS? Or have I likely got some problem with my A* - maybe poorly chosen heuristics or movement cost? Currently my movement cost is the length of the jump (the DB dump has solar system coordinates as well), and the heuristic is a quick euclidean calculation from the node to the goal. In case anyone has some optimizations for my A*, here is the routine that consumes about 60% of my processing time, according to my profiler. The coordinateData table contains a list of every system's coordinates, and neighborNode.distance is the distance of the jump. Private Function findDistance(ByVal startSystem As Integer, ByVal endSystem As Integer) As Integer 'hCount += 1 'If hCount Mod 0 = 0 Then 'Return hCache 'End If 'Initialize variables to be filled Dim x1, x2, y1, y2, z1, z2 As Integer 'LINQ queries for solar system data Dim systemFromData = From result In jumpDataDB.coordinateDatas Where result.systemId = startSystem Select result.x, result.y, result.z Dim systemToData = From result In jumpDataDB.coordinateDatas Where result.systemId = endSystem Select result.x, result.y, result.z 'LINQ execute 'Fill variables with solar system data for from and to system For Each solarSystem In systemFromData x1 = (solarSystem.x) y1 = (solarSystem.y) z1 = (solarSystem.z) Next For Each solarSystem In systemToData x2 = (solarSystem.x) y2 = (solarSystem.y) z2 = (solarSystem.z) Next Dim x3 = Math.Abs(x1 - x2) Dim y3 = Math.Abs(y1 - y2) Dim z3 = Math.Abs(z1 - z2) 'Calculate distance and round 'Dim distance = Math.Round(Math.Sqrt(Math.Abs((x1 - x2) ^ 2) + Math.Abs((y1 - y2) ^ 2) + Math.Abs((z1 - z2) ^ 2))) Dim distance = firstConstant * Math.Min(secondConstant * (x3 + y3 + z3), Math.Max(x3, Math.Max(y3, z3))) 'Dim distance = Math.Abs(x1 - x2) + Math.Abs(z1 - z2) + Math.Abs(y1 - y2) 'hCache = distance Return distance End Function And the main loop, the other 30% 'Begin search While openList.Count() != 0 'Set current system and move node to closed currentNode = lowestF() move(currentNode.id) For Each neighborNode In neighborNodes If Not onList(neighborNode.toSystem, 0) Then If Not onList(neighborNode.toSystem, 1) Then Dim newNode As New nodeData() newNode.id = neighborNode.toSystem newNode.parent = currentNode.id newNode.g = currentNode.g + neighborNode.distance newNode.h = findDistance(newNode.id, endSystem) newNode.f = newNode.g + newNode.h newNode.security = neighborNode.security openList.Add(newNode) shortOpenList(OLindex) = newNode.id OLindex += 1 Else Dim proposedG As Integer = currentNode.g + neighborNode.distance If proposedG < gValue(neighborNode.toSystem) Then changeParent(neighborNode.toSystem, currentNode.id, proposedG) End If End If End If Next 'Check to see if done If currentNode.id = endSystem Then Exit While End If End While If clarification is needed on my spaghetti code, I'll try to explain.

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  • Oracle Cloud Hiring Event at Oracle in Redwood on November 9th

    - by user769227
    Wow, 24 hours to go until Cloud Hire 2012 at Oracle! Friday is going to be a great day for many looking to make a life and career changing move. In case you haven’t heard, Oracle is hosting Cloud Hire 2012 this Friday, November 9, at the Oracle Conference Center on our World Wide Headquarters campus in Redwood Shores. This is a one-of-a-kind event to be sure and we are still registering online! We are aggressively expanding our Cloud Development and Product Management organizations to meet to ever-growing demand for Oracle Cloud. And, from this event alone, we are hoping to hire 25+ Developers, Inbound and Outbound Product Managers, Technical Leaders and QA Engineers across several Oracle Cloud groups, including: · Data and Insight Services: Big Data as a Service/Business Directory · Cloud Infrastructure · Application Marketplace · Cloud Portal · Product Management and Marketing: Outbound/Inbound · Testing/Quality Assurance · Cloud Social Platform: Analytics, Media, Big Data, Text Analytics, High Performance Search, · Cloud Social Platform - Social Relationship Management: Mobile Development/Social Network Integrations Why attend this event? Just Google Larry Ellison’s 2012 OpenWorld keynote address and you will learn why! Oracle Cloud is growing every day and we are scaling, adding new products and revolutionizing and improving all areas of the Oracle Cloud. There is no company that can come close to the comprehensive product lineup, services, capabilities and global reach and delivery of Oracle’s Cloud. This why it is a great time to work for Oracle: where consistent, stable financial growth rules and high impact technological advances are occurring every day. If you are serious about managing an upward, expansive path in your career, while staying on the leading edge and making big career impacts, you should join Oracle. Whether you want to design and develop or manage Social, Infrastructure or Applications in the Cloud, you can do it all at Oracle. Whether you’re a Technical Leader, Developer, Architect or Product Manager/Strategist, we are hiring now! Come check us out on Friday, November 9 in-person and see why Oracle Cloud is the place to take your career! RSVP here: and Learn more about the hiring teams in attendance here. Here are just some of the big things happening on Friday, November 9: · 830-3pm: Registration/Refreshments, Oracle Conference Center, 350 Oracle Parkway, Redwood Shores, CA (free parking) · 9am – 3pm: Ongoing Hiring Team Discussions and Product Demos include: Social Marketing, Social Engagement, Social Monitoring, Insight / View, KPI Bundles, Business Directory, Virtualization, Messaging, Provisioning, Cloud Portal · 10:30am – Speaker: Gopalan Arun, Vice President, Oracle Cloud Development Bio: Arun has been with Oracle for 18 years+. He is a testament to the stability and career growth that you can achieve working for Oracle. Arun began as a Developer and ascended through several product organizations into key leadership roles. Over his 18 years at Oracle, he has built and shipped many Database and Middleware products. Arun is one of the founding members of the Oracle Cloud and currently leads the development of many of the core infrastructure and developer-facing services of the Oracle Cloud. Topic: Oracle Cloud for the Developer · 1pm – Speaker: Naresh Revanuru, Lead Architect, Oracle Cloud Bio: Naresh is currently leading Java, Storage and Compute services for Oracle Cloud. Naresh also helps drive decisions for broad based Cloud topics that affect multiple services. http://www.linkedin.com/in/nareshrevanuru Topic: Oracle Cloud Architectural Overview and Challenges to Solve · 1pm-3pm: Ongoing Hiring Team Discussions and Product Demos

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  • Oracle and Partners release CAMP specification for PaaS Management

    - by macoracle
    Cloud Application Management for Platforms The public release of the Cloud Application Management for Platforms (CAMP) specification, an initial draft of what is expected to become an industry standard self service interface specification for Platform as a Service (PaaS) management, represents a significant milestone in cloud standards development. Created by several players in the emerging cloud industry, including Oracle, the specification is being submitted to the OASIS standards organization (draft charter) where it will be finalized in an open development process. CAMP is targeted at application developers and deployers for self service management of their application on a Platform-as-a-Service cloud. It is closely aligned with the application development process where applications are typically developed in an Application Development Environment (ADE) and then deployed into a private or public platform cloud. CAMP standardizes the model behind an application’s dependencies on platform components and provides a standardized format for moving applications between the ADE and the cloud, and if and when desirable, between clouds. Once an application is deployed, CAMP provides users with a standardized self service interface to the PaaS offering, allowing the cloud consumer to manage the lifecycle of the application on that platform and the use of the underlying platform services. The CAMP interface includes a RESTful binding of the CAMP model onto the standard HTTP protocol, using JSON as the encoding for the model resources. The model for CAMP includes resources that represent the Application, its Components and any Platform Components that they depend on. It's important PaaS Cloud consumers understand that for a PaaS cloud, these are the abstractions that the user would prefer to work with, not Virtual Machines and the various resources such as compute power, storage and networking. PaaS cloud consumers would also not like to become system administrators for the infrastructure that is hosting their applications and component services. CAMP works on this more abstract level, and yet still accommodates platforms that are built using an underlying infrastructure cloud. With CAMP, it is up to the cloud provider whether or not this underlying infrastructure is exposed to the consumer. One major challenge addressed by the CAMP specification is that of ensuring that application deployment on a new platform is as seamless and error free as possible. This becomes even more difficult when the application may have been developed for a different platform and is now moving to a new one. In CAMP this is accomplished by matching the requirements of the application and its components to the specific capabilities of the underlying platform. This needs to be done regardless of whether there are existing pools of virtualized platform resources (such as a database pool) which are provisioned(on the basis of a schema for example), or whether the platform component is really just a set of virtual machines drawn from an infrastructure pool. The interoperability between platform clouds that CAMP offers means that a CAMP client such as an ADE can target multiple clouds with a single common interface. Applications can even be spread across multiple platform clouds and then managed without needing to create a specialized adapter to manage the components running in each cloud. The development of CAMP has been an effort by a small set of companies, but there are significant advantages to this approach. For example, the way that each of these companies creates their platforms is different enough, to ensure that CAMP can cover a wide range of actual deployments. CAMP is now entering the next phase of development under the guidance of an open standards organization, OASIS, which will likely broaden it’s capabilities. We hope is to keep it concise and minimal, however, to ease implementation and adoption. Over time there will be many different types of platform components that applications can use and which need management. CAMP at this point only includes one example of this (in an appendix) – DataBase as a Service. I am looking forward to the start of the CAMP Technical Committee in OASIS and will do my best to ensure a successful development process. Hope to see you there.

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  • MD5 vertex skinning problem extending to multi-jointed skeleton (GPU Skinning)

    - by Soapy
    Currently I'm trying to implement GPU skinning in my project. So far I have achieved single joint translation and rotation, and multi-jointed translation. The problem arises when I try to rotate a multi-jointed skeleton. The image above shows the current progress. The left image shows how the model should deform. The middle image shows how it deforms in my project. The right shows a better deform (still not right) inverting a certain value, which I will explain below. The way I get my animation data is by exporting it to the MD5 format (MD5mesh for mesh data and MD5anim for animation data). When I come to parse the animation data, for each frame, I check if the bone has a parent, if not, the data is passed in as is from the MD5anim file. If it does have a parent, I transform the bones position by the parents orientation, and the add this with the parents translation. Then the parent and child orientations get concatenated. This is covered at this website. if (Parent < 0){ ... // Save this data without editing it } else { Math3::vec3 rpos; Math3::quat pq = Parent.Quaternion; Math3::quat pqi(pq); pqi.InvertUnitQuat(); pqi.Normalise(); Math3::quat::RotateVector3(rpos, pq, jv); Math3::vec3 npos(rpos + Parent.Pos); this->Translation = npos; Math3::quat nq = pq * jq; nq.Normalise(); this->Quaternion = nq; } And to achieve the image to the right, all I need to do is to change Math3::quat::RotateVector3(rpos, pq, jv); to Math3::quat::RotateVector3(rpos, pqi, jv);, why is that? And this is my skinning shader. SkinningShader.vert #version 330 core smooth out vec2 vVaryingTexCoords; smooth out vec3 vVaryingNormals; smooth out vec4 vWeightColor; uniform mat4 MV; uniform mat4 MVP; uniform mat4 Pallete[55]; uniform mat4 invBindPose[55]; layout(location = 0) in vec3 vPos; layout(location = 1) in vec2 vTexCoords; layout(location = 2) in vec3 vNormals; layout(location = 3) in int vSkeleton[4]; layout(location = 4) in vec3 vWeight; void main() { vec4 wpos = vec4(vPos, 1.0); vec4 norm = vec4(vNormals, 0.0); vec4 weight = vec4(vWeight, (1.0f-(vWeight[0] + vWeight[1] + vWeight[2]))); normalize(weight); mat4 BoneTransform; for(int i = 0; i < 4; i++) { if(vSkeleton[i] != -1) { if(i == 0) { // These are interchangable for some reason // BoneTransform = ((invBindPose[vSkeleton[i]] * Pallete[vSkeleton[i]]) * weight[i]); BoneTransform = ((Pallete[vSkeleton[i]] * invBindPose[vSkeleton[i]]) * weight[i]); } else { // These are interchangable for some reason // BoneTransform += ((invBindPose[vSkeleton[i]] * Pallete[vSkeleton[i]]) * weight[i]); BoneTransform += ((Pallete[vSkeleton[i]] * invBindPose[vSkeleton[i]]) * weight[i]); } } } wpos = BoneTransform * wpos; vWeightColor = weight; vVaryingTexCoords = vTexCoords; vVaryingNormals = normalize(vec3(vec4(vNormals, 0.0) * MV)); gl_Position = wpos * MVP; } The Pallete matrices are the matrices calculated using the above code (a rotation and translation matrix get created from the translation and quaternion). The invBindPose matrices are simply the inverted matrices created from the joints in the MD5mesh file. Update 1 I looked at GLM to compare the values I get with my own implementation. They turn out to be exactly the same. So now i'm checking if there's a problem with matrix creation... Update 2 Looked at GLM again to compare matrix creation using quaternions. Turns out that's not the problem either.

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  • Normal maps red in OpenGL?

    - by KaiserJohaan
    I am using Assimp to import 3d models, and FreeImage to parse textures. The problem I am having is that the normal maps are actually red rather than blue when I try to render them as normal diffuse textures. http://i42.tinypic.com/289ing3.png When I open the images in a image-viewing program they do indeed show up as blue. Heres when I create the texture; OpenGLTexture::OpenGLTexture(const std::vector<uint8_t>& textureData, uint32_t textureWidth, uint32_t textureHeight, TextureType textureType, Logger& logger) : mLogger(logger), mTextureID(gNextTextureID++), mTextureType(textureType) { glGenTextures(1, &mTexture); CHECK_GL_ERROR(mLogger); glBindTexture(GL_TEXTURE_2D, mTexture); CHECK_GL_ERROR(mLogger); glTexImage2D(GL_TEXTURE_2D, 0, GL_RGBA, textureWidth, textureHeight, 0, glTextureFormat, GL_UNSIGNED_BYTE, &textureData[0]); CHECK_GL_ERROR(mLogger); glGenerateMipmap(GL_TEXTURE_2D); CHECK_GL_ERROR(mLogger); glBindTexture(GL_TEXTURE_2D, 0); CHECK_GL_ERROR(mLogger); } Here is my fragment shader. You can see I just commented out the normal-map parsing and treated the normal map texture as the diffuse texture to display it and illustrate the problem. As for the rest of the code it interacts as expected with the diffuse textures so I dont see a obvious problem there. "#version 330 \n \ \n \ layout(std140) uniform; \n \ \n \ const int MAX_LIGHTS = 8; \n \ \n \ struct Light \n \ { \n \ vec4 mLightColor; \n \ vec4 mLightPosition; \n \ vec4 mLightDirection; \n \ \n \ int mLightType; \n \ float mLightIntensity; \n \ float mLightRadius; \n \ float mMaxDistance; \n \ }; \n \ \n \ uniform UnifLighting \n \ { \n \ vec4 mGamma; \n \ vec3 mViewDirection; \n \ int mNumLights; \n \ \n \ Light mLights[MAX_LIGHTS]; \n \ } Lighting; \n \ \n \ uniform UnifMaterial \n \ { \n \ vec4 mDiffuseColor; \n \ vec4 mAmbientColor; \n \ vec4 mSpecularColor; \n \ vec4 mEmissiveColor; \n \ \n \ bool mHasDiffuseTexture; \n \ bool mHasNormalTexture; \n \ bool mLightingEnabled; \n \ float mSpecularShininess; \n \ } Material; \n \ \n \ uniform sampler2D unifDiffuseTexture; \n \ uniform sampler2D unifNormalTexture; \n \ \n \ in vec3 frag_position; \n \ in vec3 frag_normal; \n \ in vec2 frag_texcoord; \n \ in vec3 frag_tangent; \n \ in vec3 frag_bitangent; \n \ \n \ out vec4 finalColor; " " \n \ \n \ void CalcGaussianSpecular(in vec3 dirToLight, in vec3 normal, out float gaussianTerm) \n \ { \n \ vec3 viewDirection = normalize(Lighting.mViewDirection); \n \ vec3 halfAngle = normalize(dirToLight + viewDirection); \n \ \n \ float angleNormalHalf = acos(dot(halfAngle, normalize(normal))); \n \ float exponent = angleNormalHalf / Material.mSpecularShininess; \n \ exponent = -(exponent * exponent); \n \ \n \ gaussianTerm = exp(exponent); \n \ } \n \ \n \ vec4 CalculateLighting(in Light light, in vec4 diffuseTexture, in vec3 normal) \n \ { \n \ if (light.mLightType == 1) // point light \n \ { \n \ vec3 positionDiff = light.mLightPosition.xyz - frag_position; \n \ float dist = max(length(positionDiff) - light.mLightRadius, 0); \n \ \n \ float attenuation = 1 / ((dist/light.mLightRadius + 1) * (dist/light.mLightRadius + 1)); \n \ attenuation = max((attenuation - light.mMaxDistance) / (1 - light.mMaxDistance), 0); \n \ \n \ vec3 dirToLight = normalize(positionDiff); \n \ float angleNormal = clamp(dot(normalize(normal), dirToLight), 0, 1); \n \ \n \ float gaussianTerm = 0.0; \n \ if (angleNormal > 0.0) \n \ CalcGaussianSpecular(dirToLight, normal, gaussianTerm); \n \ \n \ return diffuseTexture * (attenuation * angleNormal * Material.mDiffuseColor * light.mLightIntensity * light.mLightColor) + \n \ (attenuation * gaussianTerm * Material.mSpecularColor * light.mLightIntensity * light.mLightColor); \n \ } \n \ else if (light.mLightType == 2) // directional light \n \ { \n \ vec3 dirToLight = normalize(light.mLightDirection.xyz); \n \ float angleNormal = clamp(dot(normalize(normal), dirToLight), 0, 1); \n \ \n \ float gaussianTerm = 0.0; \n \ if (angleNormal > 0.0) \n \ CalcGaussianSpecular(dirToLight, normal, gaussianTerm); \n \ \n \ return diffuseTexture * (angleNormal * Material.mDiffuseColor * light.mLightIntensity * light.mLightColor) + \n \ (gaussianTerm * Material.mSpecularColor * light.mLightIntensity * light.mLightColor); \n \ } \n \ else if (light.mLightType == 4) // ambient light \n \ return diffuseTexture * Material.mAmbientColor * light.mLightIntensity * light.mLightColor; \n \ else \n \ return vec4(0.0); \n \ } \n \ \n \ void main() \n \ { \n \ vec4 diffuseTexture = vec4(1.0); \n \ if (Material.mHasDiffuseTexture) \n \ diffuseTexture = texture(unifDiffuseTexture, frag_texcoord); \n \ \n \ vec3 normal = frag_normal; \n \ if (Material.mHasNormalTexture) \n \ { \n \ diffuseTexture = vec4(normalize(texture(unifNormalTexture, frag_texcoord).xyz * 2.0 - 1.0), 1.0); \n \ // vec3 normalTangentSpace = normalize(texture(unifNormalTexture, frag_texcoord).xyz * 2.0 - 1.0); \n \ //mat3 tangentToWorldSpace = mat3(normalize(frag_tangent), normalize(frag_bitangent), normalize(frag_normal)); \n \ \n \ // normal = tangentToWorldSpace * normalTangentSpace; \n \ } \n \ \n \ if (Material.mLightingEnabled) \n \ { \n \ vec4 accumLighting = vec4(0.0); \n \ \n \ for (int lightIndex = 0; lightIndex < Lighting.mNumLights; lightIndex++) \n \ accumLighting += Material.mEmissiveColor * diffuseTexture + \n \ CalculateLighting(Lighting.mLights[lightIndex], diffuseTexture, normal); \n \ \n \ finalColor = pow(accumLighting, Lighting.mGamma); \n \ } \n \ else { \n \ finalColor = pow(diffuseTexture, Lighting.mGamma); \n \ } \n \ } \n"; Why is this? does normal-map textures need some sort of special treatment in opengl?

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  • SQL analytical mash-ups deliver real-time WOW! for big data

    - by KLaker
    One of the overlooked capabilities of SQL as an analysis engine, because we all just take it for granted, is that you can mix and match analytical features to create some amazing mash-ups. As we move into the exciting world of big data these mash-ups can really deliver those "wow, I never knew that" moments. While Java is an incredibly flexible and powerful framework for managing big data there are some significant challenges in using Java and MapReduce to drive your analysis to create these "wow" discoveries. One of these "wow" moments was demonstrated at this year's OpenWorld during Andy Mendelsohn's general keynote session.  Here is the scenario - we are looking for fraudulent activities in our big data stream and in this case we identifying potentially fraudulent activities by looking for specific patterns. We using geospatial tagging of each transaction so we can create a real-time fraud-map for our business users. Where we start to move towards a "wow" moment is to extend this basic use of spatial and pattern matching, as shown in the above dashboard screen, to incorporate spatial analytics within the SQL pattern matching clause. This will allow us to compute the distance between transactions. Apologies for the quality of this screenshot….hopefully below you see where we have extended our SQL pattern matching clause to use location of each transaction and to calculate the distance between each transaction: This allows us to compare the time of the last transaction with the time of the current transaction and see if the distance between the two points is possible given the time frame. Obviously if I buy something in Florida from my favourite bike store (may be a new carbon saddle for my Trek) and then 5 minutes later the system sees my credit card details being used in Arizona there is high probability that this transaction in Arizona is actually fraudulent (I am fast on my Trek but not that fast!) and we can flag this up in real-time on our dashboard: In this post I have used the term "real-time" a couple of times and this is an important point and one of the key reasons why SQL really is the only language to use if you want to analyse  big data. One of the most important questions that comes up in every big data project is: how do we do analysis? Many enlightened customers are now realising that using Java-MapReduce to deliver analysis does not result in "wow" moments. These "wow" moments only come with SQL because it is offers a much richer environment, it is simpler to use and it is faster - which makes it possible to deliver real-time "Wow!". Below is a slide from Andy's session showing the results of a comparison of Java-MapReduce vs. SQL pattern matching to deliver our "wow" moment during our live demo.  You can watch our analytical mash-up "Wow" demo that compares the power of 12c SQL pattern matching + spatial analytics vs. Java-MapReduce  here: You can get more information about SQL Pattern Matching on our SQL Analytics home page on OTN, see here http://www.oracle.com/technetwork/database/bi-datawarehousing/sql-analytics-index-1984365.html.  You can get more information about our spatial analytics here: http://www.oracle.com/technetwork/database-options/spatialandgraph/overview/index.html If you would like to watch the full Database 12c OOW presentation see here: http://medianetwork.oracle.com/video/player/2686974264001

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  • CSM DX11 issues

    - by KaiserJohaan
    I got CSM to work in OpenGL, and now Im trying to do the same in directx. I'm using the same math library and all and I'm pretty much using the alghorithm straight off. I am using right-handed, column major matrices from GLM. The light is looking (-1, -1, -1). The problem I have is twofolds; For some reason, the ground floor is causing alot of (false) shadow artifacts, like the vast shadowed area you see. I confirmed this when I disabled the ground for the depth pass, but thats a hack more than anything else The shadows are inverted compared to the shadowmap. If you squint you can see the chairs shadows should be mirrored instead. This is the first cascade shadow map, in range of the alien and the chair: I can't figure out why this is. This is the depth pass: for (uint32_t cascadeIndex = 0; cascadeIndex < NUM_SHADOWMAP_CASCADES; cascadeIndex++) { mShadowmap.BindDepthView(context, cascadeIndex); CameraFrustrum cameraFrustrum = CalculateCameraFrustrum(degreesFOV, aspectRatio, nearDistArr[cascadeIndex], farDistArr[cascadeIndex], cameraViewMatrix); lightVPMatrices[cascadeIndex] = CreateDirLightVPMatrix(cameraFrustrum, lightDir); mVertexTransformPass.RenderMeshes(context, renderQueue, meshes, lightVPMatrices[cascadeIndex]); lightVPMatrices[cascadeIndex] = gBiasMatrix * lightVPMatrices[cascadeIndex]; farDistArr[cascadeIndex] = -farDistArr[cascadeIndex]; } CameraFrustrum CalculateCameraFrustrum(const float fovDegrees, const float aspectRatio, const float minDist, const float maxDist, const Mat4& cameraViewMatrix) { CameraFrustrum ret = { Vec4(1.0f, 1.0f, -1.0f, 1.0f), Vec4(1.0f, -1.0f, -1.0f, 1.0f), Vec4(-1.0f, -1.0f, -1.0f, 1.0f), Vec4(-1.0f, 1.0f, -1.0f, 1.0f), Vec4(1.0f, -1.0f, 1.0f, 1.0f), Vec4(1.0f, 1.0f, 1.0f, 1.0f), Vec4(-1.0f, 1.0f, 1.0f, 1.0f), Vec4(-1.0f, -1.0f, 1.0f, 1.0f), }; const Mat4 perspectiveMatrix = PerspectiveMatrixFov(fovDegrees, aspectRatio, minDist, maxDist); const Mat4 invMVP = glm::inverse(perspectiveMatrix * cameraViewMatrix); for (Vec4& corner : ret) { corner = invMVP * corner; corner /= corner.w; } return ret; } Mat4 CreateDirLightVPMatrix(const CameraFrustrum& cameraFrustrum, const Vec3& lightDir) { Mat4 lightViewMatrix = glm::lookAt(Vec3(0.0f), -glm::normalize(lightDir), Vec3(0.0f, -1.0f, 0.0f)); Vec4 transf = lightViewMatrix * cameraFrustrum[0]; float maxZ = transf.z, minZ = transf.z; float maxX = transf.x, minX = transf.x; float maxY = transf.y, minY = transf.y; for (uint32_t i = 1; i < 8; i++) { transf = lightViewMatrix * cameraFrustrum[i]; if (transf.z > maxZ) maxZ = transf.z; if (transf.z < minZ) minZ = transf.z; if (transf.x > maxX) maxX = transf.x; if (transf.x < minX) minX = transf.x; if (transf.y > maxY) maxY = transf.y; if (transf.y < minY) minY = transf.y; } Mat4 viewMatrix(lightViewMatrix); viewMatrix[3][0] = -(minX + maxX) * 0.5f; viewMatrix[3][1] = -(minY + maxY) * 0.5f; viewMatrix[3][2] = -(minZ + maxZ) * 0.5f; viewMatrix[0][3] = 0.0f; viewMatrix[1][3] = 0.0f; viewMatrix[2][3] = 0.0f; viewMatrix[3][3] = 1.0f; Vec3 halfExtents((maxX - minX) * 0.5, (maxY - minY) * 0.5, (maxZ - minZ) * 0.5); return OrthographicMatrix(-halfExtents.x, halfExtents.x, -halfExtents.y, halfExtents.y, halfExtents.z, -halfExtents.z) * viewMatrix; } And this is the pixel shader used for the lighting stage: #define DEPTH_BIAS 0.0005 #define NUM_CASCADES 4 cbuffer DirectionalLightConstants : register(CBUFFER_REGISTER_PIXEL) { float4x4 gSplitVPMatrices[NUM_CASCADES]; float4x4 gCameraViewMatrix; float4 gSplitDistances; float4 gLightColor; float4 gLightDirection; }; Texture2D gPositionTexture : register(TEXTURE_REGISTER_POSITION); Texture2D gDiffuseTexture : register(TEXTURE_REGISTER_DIFFUSE); Texture2D gNormalTexture : register(TEXTURE_REGISTER_NORMAL); Texture2DArray gShadowmap : register(TEXTURE_REGISTER_DEPTH); SamplerComparisonState gShadowmapSampler : register(SAMPLER_REGISTER_DEPTH); float4 ps_main(float4 position : SV_Position) : SV_Target0 { float4 worldPos = gPositionTexture[uint2(position.xy)]; float4 diffuse = gDiffuseTexture[uint2(position.xy)]; float4 normal = gNormalTexture[uint2(position.xy)]; float4 camPos = mul(gCameraViewMatrix, worldPos); uint index = 3; if (camPos.z > gSplitDistances.x) index = 0; else if (camPos.z > gSplitDistances.y) index = 1; else if (camPos.z > gSplitDistances.z) index = 2; float3 projCoords = (float3)mul(gSplitVPMatrices[index], worldPos); float viewDepth = projCoords.z - DEPTH_BIAS; projCoords.z = float(index); float visibilty = gShadowmap.SampleCmpLevelZero(gShadowmapSampler, projCoords, viewDepth); float angleNormal = clamp(dot(normal, gLightDirection), 0, 1); return visibilty * diffuse * angleNormal * gLightColor; } As you can see I am using depth bias and a bias matrix. Any hints on why this behaves so wierdly?

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  • MPI Cluster Debugger launch integration in VS2010

    Let's assume that you have all the HPC bits installed and that you have existing MPI code (or you created a "Hello World" project using the MPI project template). Of course, you create a single MPI application and at runtime it will correspond to multiple processes (of the same app) launched on multiple nodes (i.e. machines) on the cluster. So how do you debug such a situation by simply hitting the familiar "F5" keystroke (i.e. Debug - Start Debugging)?WATCH IT INSTEAD OF READING ABOUT ITIf you can't bear to read through all the details below, just watch this 19-minute screencast explaining this VS2010 feature. Alternatively, or even additionally, keep on reading.REQUIREMENTWhen you debug an MPI application, you would want the copying of resources from your client machine (where Visual Studio is installed) to each compute node (where Windows HPC Server is installed) to take place automatically for you. 'Resources' in the previous sentence includes your application binary, plus any binary or data dependencies it may have, plus PDBs if needed, plus the debug CRT of the correct bitness, plus msvsmon for remote debugging to work. You would also want, after copying is complete, to have your app and msvsmon launched and attached so that you can hit breakpoints back in Visual Studio on your client machine. All these thing that you would want are delivered in VS2010.STEPS TO F51. In your MPI project where you have placed a breakpoint go to Project Properties - Configuration Properties - Debugging. Ensure the "Debugger to launch" combo box value is set to MPI Cluster Debugger.2. There are a whole bunch of properties here and typically you can ignore all of them except one: Run Environment. By default it is set to run 1 process on your local machine and if you change the number after that to, for example, 4 it will launch 4 processes of your app on your local machine.You want this to run on your cluster though, so go to the dropdown arrow at the end of the Run Environment cell and open it to expose the "Edit Hpc node" menu which opens the Node Selector dialog:In this dialog you can enter (or pick from a list) the cluster head node name and then the number of processes you want to execute on the cluster and then hit OK and… you are done.3. Press F5 and watch your breakpoint get hit (after giving it some time for copying, remote execution, attachment and symbol resolution to take place).GOING DEEPERIn the MPI Cluster Debugger project properties above, you can see many additional properties to the Run Environment. They are all optional, but you may want to understand them in order to fine tune your cluster debugging. Read all about each one of these on the MSDN page Configuration Properties for the MPI Cluster Debugger.In the Node Selector dialog above you can see more options than just the Head Node name and Number of Process to run. They should be self-explanatory but I also cover them in depth in my screencast showing you an example of why you would choose to schedule processes per core versus per node. You can also read about these options on MSDN as part of the page How to: Configure and Launch the MPI Cluster Debugger.To read through an example that touches on MPI project creation, project properties, node selector, and also usage of MPI with OpenMP plus MPI with PPL, read the MSDN page Walkthrough: Launching the MPI Cluster Debugger in Visual Studio 2010.Happy MPI debugging! Comments about this post welcome at the original blog.

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  • Exalytics and Oracle Business Intelligence Enterprise Edition (OBIEE) Partner Workshop

    - by mseika
    Workshop Description Oracle Fusion Middleware 11g is the #1 application infrastructure foundation. It enables enterprises to create and run agile and intelligent business applications and maximize IT efficiency by exploiting modern hardware and software architectures. Oracle Exalytics Business Intelligence Machine is the world’s first engineered system specifically designed to deliver high performance analysis, modeling and planning. Built using industry-standard hardware, market-leading business intelligence software and in-memory database technology, Oracle Exalytics is an optimized system that delivers unmatched speed, visualizations and scalability for Business Intelligence and Enterprise Performance Management applications. This FREE hands-on, partner workshop highlights both the hardware and software components that are engineered to work together to deliver Oracle Exalytics - an optimized version of the industry-leading Oracle TimesTen In-Memory Database with analytic extensions, a highly scalable Oracle server designed specifically for in-memory business intelligence, and Oracle’s proven Business Intelligence Foundation with enhanced visualization capabilities and performance optimizations. This workshop will provide hands-on experience with Oracle's latest engineered system. Topics covered will include TimesTen In-Memory Database and the new Summary Advisor for Exalytics, the technical details (including mobile features) of the latest release of visualization enhancements for OBI-EE, and technical updates on Essbase. After taking this course, you will be well prepared to architect, build, demo, and implement an end-to-end Exalytics solution. You will also be able to extend your current analytical and enterprise performance management application implementations with numerous Oracle technologies specifically enhanced to take advantage of the compute capacity and in-memory capabilities of Oracle Exalytics.If you are a BI or Data Warehouse Architect, developer or consultant, you don’t want to miss this 3-day workshop. Register Now! Presentations Exalytics Architectural Overview Upgrade and Lifecycle Management Times Ten for Exalytics Summary Advisor Utility Essbase and EPM System on Exalytics Dashboard and Analysis Interactions OBIEE 11.1.1.6 Features and Advanced Topics Lab OutlineThe labs showcase Oracle Exalytics core components and functionality and provide expertise of Oracle Business Intelligence 11.1.1.6 new features and updates from prior releases. The hands-on activities are based on an Oracle VirtualBox image with software and training samples pre-installed. Lab Environment Setup Creating and Working with Oracle TimesTen In-Memory Database Running Summary Advisor Utility Working with Exalytics Visualization Features – Dashboard and Analysis Interactions Audience Oracle Partners BI and EPM Application Developers and Implementers System Integrators and Solution Consultants Data Warehouse Developers Enterprise Architects Prerequisites Experience and understanding of OBIEE 11g is required Previous attendance of Oracle Business Intelligence Foundation Suite Workshop or BIEE 11gIntroduction Workshop is highly recommended Good understanding of data warehousing and data modeling for reporting and analysis purpose Strong experience with database technologies preferred Equipment RequirementsThis workshop requires attendees to provide their own laptops for this class.Attendee laptops must meet the following minimum hardware/software requirements: Hardware Minimum 8GB RAM 60 GB free space (includes staging) USB 2.0 port (at least one available) It is strongly recommended that you bring a mouse. You will be working in a development environment and using the mouse heavily. Software One of the following operating systems: 64-bit Windows host/laptop OS 64-bit host/laptop OS with a Windows VM (XP, Server, or Win 7, BIC2g, etc.) Internet Explorer 7.x/8.x or Firefox 3.5.x WINRAR or 7ziputility to unzip workshop files: Download-able from http://www.win-rar.com/download.html Download-able from http://www.7zip.com/ Oracle VirtualBox 4.0.2 or higher Downloadable from http://www.virtualbox.org/wiki/Downloads CPU virtualization mode needs to be enabled. We will provide guidance on the day of the workshop. Attendees will be given a VirtualBox image containing a pre-installed Oracle Exalytics environment. Schedule This workshop is 3 days. - Times vary by country!9:00am: Sign-in and technical setup 9:30am: Workshop starts 5:00pm: Workshop ends Oracle Exalytics and Business Intelligence (OBIEE) Workshop December 11-13, 2012: Oracle BVP, Birmingham, UK Register Here. Questions? Send email to: [email protected] Oracle Platform Technologies Enablement Services

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  • Windows Azure SDK 1.3 addresses early adopter feedback

    - by Eric Nelson
    At the end of November 2010 we released a new version of the Windows Azure SDK which contains many new features driven by the great feedback of early adopters plus a shiny new portal. New Portal implemented in Silverlight: The new portal is implemented using Silverlight and replaces the (IMHO rather clunky) original HTML + JavaScript portal. It is 100% better although does still have a few bugs. Enjoy! P.S. You can if you wish still use the old portal:   New runtime functionality: The following functionality is now generally available through the Windows Azure SDK and Windows Azure Tools for Visual Studio and the new Windows Azure Management Portal: Elevated Privileges and Full IIS. You can now run a portion or all of your code in Web and Worker roles with elevated administrator privileges. The Web role now provides Full IIS functionality, which enables multiple IIS sites per Web role and the ability to install IIS modules. Remote Desktop functionality enables you to connect to a running instance of your application or service in order to monitor activity and troubleshoot common problems. Windows Server 2008 R2 Roles: Windows Azure now supports Windows Server 2008 R2 in its Web, worker and VM roles. This new support enables you to take advantage of the full range of Windows Server 2008 R2 features such as IIS 7.5, AppLocker, and enhanced command-line and automated management using PowerShell Version 2.0. New runtime functionality – in beta: Windows Azure Virtual Machine Role: Support for more types of new and existing Windows applications will soon be available with the introduction of the Virtual Machine (VM) role. You can move more existing applications to Windows Azure, reducing the need to make costly code or deployment changes. Extra Small Windows Azure Instance, which is priced at $0.05 per compute hour, provides developers with a cost-effective training and development environment. Developers can also use the Extra Small instance to prototype cloud solutions at a lower cost. Windows Azure Connect: (formerly Project Sydney), which enables a simple and easy-to-manage mechanism to set up IP-based network connectivity between on-premises and Windows Azure resources, is the first Windows Azure Virtual Network feature that we’re making available as a CTP. You can sign up for any of the betas via the Windows Azure Management Portal. Improved processes and simplified operations New portal! (see above) Access to new diagnostic information including the ability to click on a role to see role type, deployment time and last reboot time A new sign-up process that dramatically reduces the number of steps needed to sign up for Windows Azure. New scenario based Windows Azure Platform forums to help answer questions and share knowledge more efficiently. Multiple Service Administrators: Windows Azure now supports multiple Windows Live IDs to have administrator privileges on the same Windows Azure account. The objective is to make it easy for a team to work on the same Windows Azure account while using their individual Windows Live IDs.   Related Links Please also let us know through Microsoft Platform Ready if and when you intend to build an application using the Windows Azure Platform. Or indeed if you already have (Well done). You will get access to some great benefits if you do (more on that in a future post). It also really helps us better understand the demand out there which directly impacts how we will plan the next six months of activities around the Windows Azure Platform. Visit Microsoft Platform Ready to tell us about your plans for your applications UK based? Interested in the Windows Azure Platform? Join http://ukazure.ning.com Get started with the Windows Azure Platform http://bit.ly/startazure

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  • Nothing drawing on screen OpenGL with GLSL

    - by codemonkey
    I hate to be asking this kind of question here, but I am at a complete loss as to what is going wrong, so please bear with me. I am trying to render a single cube (voxel) in the center of the screen, through OpenGL with GLSL on Mac I begin by setting up everything using glut glutInit(&argc, argv); glutInitDisplayMode(GLUT_RGBA|GLUT_ALPHA|GLUT_DOUBLE|GLUT_DEPTH); glutInitWindowSize(DEFAULT_WINDOW_WIDTH, DEFAULT_WINDOW_HEIGHT); glutCreateWindow("Cubez-OSX"); glutReshapeFunc(reshape); glutDisplayFunc(render); glutIdleFunc(idle); _electricSheepEngine=new ElectricSheepEngine(DEFAULT_WINDOW_WIDTH, DEFAULT_WINDOW_HEIGHT); _electricSheepEngine->initWorld(); glutMainLoop(); Then inside the engine init camera & projection matrices: cameraPosition=glm::vec3(2,2,2); cameraTarget=glm::vec3(0,0,0); cameraUp=glm::vec3(0,0,1); glm::vec3 cameraDirection=glm::normalize(cameraPosition-cameraTarget); cameraRight=glm::cross(cameraDirection, cameraUp); cameraRight.z=0; view=glm::lookAt(cameraPosition, cameraTarget, cameraUp); lensAngle=45.0f; aspectRatio=1.0*(windowWidth/windowHeight); nearClippingPlane=0.1f; farClippingPlane=100.0f; projection=glm::perspective(lensAngle, aspectRatio, nearClippingPlane, farClippingPlane); then init shaders and check compilation and bound attributes & uniforms to be correctly bound (my previous question) These are my two shaders, vertex: #version 120 attribute vec3 position; attribute vec3 inColor; uniform mat4 mvp; varying vec3 fragColor; void main(void){ fragColor = inColor; gl_Position = mvp * vec4(position, 1.0); } and fragment: #version 120 varying vec3 fragColor; void main(void) { gl_FragColor = vec4(fragColor,1.0); } init the cube: setPosition(glm::vec3(0,0,0)); struct voxelData data[]={ //front face {{-1.0, -1.0, 1.0}, {0.0, 0.0, 1.0}}, {{ 1.0, -1.0, 1.0}, {0.0, 1.0, 1.0}}, {{ 1.0, 1.0, 1.0}, {0.0, 0.0, 1.0}}, {{-1.0, 1.0, 1.0}, {0.0, 1.0, 1.0}}, //back face {{-1.0, -1.0, -1.0}, {0.0, 0.0, 1.0}}, {{ 1.0, -1.0, -1.0}, {0.0, 1.0, 1.0}}, {{ 1.0, 1.0, -1.0}, {0.0, 0.0, 1.0}}, {{-1.0, 1.0, -1.0}, {0.0, 1.0, 1.0}} }; glGenBuffers(1, &modelVerticesBufferObject); glBindBuffer(GL_ARRAY_BUFFER, modelVerticesBufferObject); glBufferData(GL_ARRAY_BUFFER, sizeof(data), data, GL_STATIC_DRAW); glBindBuffer(GL_ARRAY_BUFFER, 0); const GLubyte indices[] = { // Front 0, 1, 2, 2, 3, 0, // Back 4, 6, 5, 4, 7, 6, // Left 2, 7, 3, 7, 6, 2, // Right 0, 4, 1, 4, 1, 5, // Top 6, 2, 1, 1, 6, 5, // Bottom 0, 3, 7, 0, 7, 4 }; glGenBuffers(1, &modelFacesBufferObject); glBindBuffer(GL_ELEMENT_ARRAY_BUFFER, modelFacesBufferObject); glBufferData(GL_ELEMENT_ARRAY_BUFFER, sizeof(indices), indices, GL_STATIC_DRAW); glBindBuffer(GL_ELEMENT_ARRAY_BUFFER, 0); and then the render call: glClearColor(0.52, 0.8, 0.97, 1.0); glClear(GL_COLOR_BUFFER_BIT | GL_DEPTH_BUFFER_BIT); glEnable(GL_DEPTH_TEST); //use the shader glUseProgram(shaderProgram); //enable attributes in program glEnableVertexAttribArray(shaderAttribute_position); glEnableVertexAttribArray(shaderAttribute_color); //model matrix using model position vector glm::mat4 mvp=projection*view*voxel->getModelMatrix(); glUniformMatrix4fv(shaderAttribute_mvp, 1, GL_FALSE, glm::value_ptr(mvp)); glBindBuffer(GL_ARRAY_BUFFER, voxel->modelVerticesBufferObject); glVertexAttribPointer(shaderAttribute_position, // attribute 3, // number of elements per vertex, here (x,y) GL_FLOAT, // the type of each element GL_FALSE, // take our values as-is sizeof(struct voxelData), // coord every (sizeof) elements 0 // offset of first element ); glBindBuffer(GL_ARRAY_BUFFER, voxel->modelVerticesBufferObject); glVertexAttribPointer(shaderAttribute_color, // attribute 3, // number of colour elements per vertex, here (x,y) GL_FLOAT, // the type of each element GL_FALSE, // take our values as-is sizeof(struct voxelData), // coord every (sizeof) elements (GLvoid *)(offsetof(struct voxelData, color3D)) // offset of colour data ); //draw the model by going through its elements array glBindBuffer(GL_ELEMENT_ARRAY_BUFFER, voxel->modelFacesBufferObject); int bufferSize; glGetBufferParameteriv(GL_ELEMENT_ARRAY_BUFFER, GL_BUFFER_SIZE, &bufferSize); glDrawElements(GL_TRIANGLES, bufferSize/sizeof(GLushort), GL_UNSIGNED_SHORT, 0); //close up the attribute in program, no more need glDisableVertexAttribArray(shaderAttribute_position); glDisableVertexAttribArray(shaderAttribute_color); but on screen all I get is the clear color :$ I generate my model matrix using: modelMatrix=glm::translate(glm::mat4(1.0), position); which in debug turns out to be for the position of (0,0,0): |1, 0, 0, 0| |0, 1, 0, 0| |0, 0, 1, 0| |0, 0, 0, 1| Sorry for such a question, I know it is annoying to look at someone's code, but I promise I have tried to debug around and figure it out as much as I can, and can't come to a solution Help a noob please? EDIT: Full source here, if anyone wants

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  • Managing Oracle Exalogic Elastic Cloud with Oracle Enterprise Manager Ops Center

    - by Anand Akela
    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:0in; mso-para-margin-bottom:.0001pt; 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-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Oracle Enterprise Manager Ops Center 12c now comes out-of-the-box  with the latest release of Oracle Exalogic Elastic Cloud 2.0.1 software. It allows Customer to manage and monitor all components inside the Exalogic rack, including provisioning and management of physical and virtualized server. Ops Center will allow Customers to easily get started with creating and managing Private Clouds using the Exalogic components. Here is a snaphot of the Assets view showing the managable components of a Quarter Rack with 8 Compute Nodes: 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:0in; mso-para-margin-bottom:.0001pt; 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-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} A colleague has recently posted an interesting series of "Exalogic 2.0.1 Tea Break Snippets" which will guide you through the initial steps to get started with setting up your Exalogic environment: Exalogic 2.0.1 Tea Break Snippets - Creating Cloud Users https://blogs.oracle.com/ATeamExalogic/entry/exalogic_2_0_1_tea1 Exalogic 2.0.1 Tea Break Snippets - Creating Networks https://blogs.oracle.com/ATeamExalogic/entry/exalogic_2_0_1_tea2 Exalogic 2.0.1 Tea Break Snippets - Allocating Static IP Addresses https://blogs.oracle.com/ATeamExalogic/entry/exalogic_2_0_1_tea3 Exalogic 2.0.1 Tea Break Snippets - Creating Accounts https://blogs.oracle.com/ATeamExalogic/entry/exalogic_2_0_1_tea4 Exalogic 2.0.1 Tea Break Snippets - Importing Public Server Template https://blogs.oracle.com/ATeamExalogic/entry/exalogic_2_0_1_tea5 Have fun reading these very useful postings ! Dr. Jürgen Fleischer , Oracle Enterprise Manager Ops Center Engineering Stay Connected: Twitter |  Face book |  You Tube |  Linked in |  Newsletter

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  • ArchBeat Link-o-Rama Top 10 for November 2012

    - by Bob Rhubart
    Every day ArchBeat searches the web for content created by and for community members, and then shares that content via social media. Here's the list of the Top 10 most popular items posted on the OTN ArchBeat Facebook Page for November 2012. One-Stop Shop for Oracle Webcasts Webcasts can be a great way to get information about Oracle products without having to go cross-eyed reading yet another document off your computer screen. Oracle's new Webcast Center offers selectable filtering to make it easy to get to the information you want. Yes, you have to register to gain access, but that process is quick, and with over 200 webcasts to choose from you know you'll find useful content. OAM/OVD JVM Tuning Vinay from the Oracle Fusion Middleware Architecture Group (otherwise known as the A-Team) shares a process for analyzing and improving performance in Oracle Virtual Directory and Oracle Access Manager. White Paper: Oracle Exalogic Elastic Cloud: Advanced I/O Virtualization Architecture for Consolidating High-Performance Workloads This new white paper by Adam Hawley (with contributions from Yoav Eilat) describes in great detail the incorporation into Oracle Exalogic of virtualized InfiniBand I/O interconnects using Single Root I/O Virtualization (SR-IOV) technology. Architected Systems: "If you don't develop an architecture, you will get one anyway..." "Can you build a system without taking care of architecture?," asks Manuel Ricca. "You certainly can. But inevitably the system will be unbalanced, neglecting the interests of key stakeholders, and problems will soon emerge." Backup and Recovery of an Exalogic vServer via rsync "On Exalogic a vServer will consist of a number of resources from the underlying machine," says the man known only as Donald. "These resources include compute power, networking and storage. In order to recover a vServer from a failure in the underlying rack all of these components have to be thoughts about. This article only discusses the backup and recovery strategies that apply to the storage system of a vServer." This Week on the OTN Architect Community Home Page Make time to check out this week's features on the OTN Solution Architect Homepage, including: SOA Practitioner Guide: Identifying and Discovering Services Technical article by Yuli Vasiliev on Setting Up, Configuring, and Using an Oracle WebLogic Server Cluster Podcast: Are You Future Proof? Clustering ODI11g for High-Availability Part 1: Introduction and Architecture | Richard Yeardley "JEE agents can be deployed alongside, or instead of, standalone agents," says Rittman Meade's Richard Yeardley. "But there is one key advantage in using JEE agents and WebLogic – when you deploy JEE agents as part of a WebLogic cluster they can be configured together to form a high availability cluster." Learn more in Yeardley's extensive post. OIM 11g : Multi-thread approach for writing custom scheduled job | Saravanan V S Saravanan shares insight and expertise relevant to "designing and developing an OIM schedule job that uses multi threaded approach for updating data in OIM using APIs." How to Create Virtual Directory in Weblogic Server | Zeeshan Baig Oracle ACE Zeeshan Baig shows you how in six easy steps. SOA Galore: New Books for Technical Eyes Only Shake up up your technical skills with this trio of new technical books from community members covering SOA and BPM. Thought for the Day "Humans are the best value in computers -- where else can you get a non-linear computer weighing only about 160lbs, having a billion binary decision elements, that can be mass-produced by unskilled labour?" — Anonymous Source: SoftwareQuotes.com

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  • Using Appendbuffers in unity for terrain generation

    - by Wardy
    Like many others I figured I would try and make the most of the monster processing power of the GPU but I'm having trouble getting the basics in place. CPU code: using UnityEngine; using System.Collections; public class Test : MonoBehaviour { public ComputeShader Generator; public MeshTopology Topology; void OnEnable() { var computedMeshPoints = ComputeMesh(); CreateMeshFrom(computedMeshPoints); } private Vector3[] ComputeMesh() { var size = (32*32) * 4; // 4 points added for each x,z pos var buffer = new ComputeBuffer(size, 12, ComputeBufferType.Append); Generator.SetBuffer(0, "vertexBuffer", buffer); Generator.Dispatch(0, 1, 1, 1); var results = new Vector3[size]; buffer.GetData(results); buffer.Dispose(); return results; } private void CreateMeshFrom(Vector3[] generatedPoints) { var filter = GetComponent<MeshFilter>(); var renderer = GetComponent<MeshRenderer>(); if (generatedPoints.Length > 0) { var mesh = new Mesh { vertices = generatedPoints }; var colors = new Color[generatedPoints.Length]; var indices = new int[generatedPoints.Length]; //TODO: build this different based on topology of the mesh being generated for (int i = 0; i < indices.Length; i++) { indices[i] = i; colors[i] = Color.blue; } mesh.SetIndices(indices, Topology, 0); mesh.colors = colors; mesh.RecalculateNormals(); mesh.Optimize(); mesh.RecalculateBounds(); filter.sharedMesh = mesh; } else { filter.sharedMesh = null; } } } GPU code: #pragma kernel Generate AppendStructuredBuffer<float3> vertexBuffer : register(u0); void genVertsAt(uint2 xzPos) { //TODO: put some height generation code here. // could even run marching cubes / dual contouring code. float3 corner1 = float3( xzPos[0], 0, xzPos[1] ); float3 corner2 = float3( xzPos[0] + 1, 0, xzPos[1] ); float3 corner3 = float3( xzPos[0], 0, xzPos[1] + 1); float3 corner4 = float3( xzPos[0] + 1, 0, xzPos[1] + 1 ); vertexBuffer.Append(corner1); vertexBuffer.Append(corner2); vertexBuffer.Append(corner3); vertexBuffer.Append(corner4); } [numthreads(32, 1, 32)] void Generate (uint3 threadId : SV_GroupThreadID, uint3 groupId : SV_GroupID) { uint2 currentXZ = unint2( groupId.x * 32 + threadId.x, groupId.z * 32 + threadId.z); genVertsAt(currentXZ); } Can anyone explain why when I call "buffer.GetData(results);" on the CPU after the compute dispatch call my buffer is full of Vector3(0,0,0), I'm not expecting any y values yet but I would expect a bunch of thread indexes in the x,z values for the Vector3 array. I'm not getting any errors in any of this code which suggests it's correct syntax-wise but maybe the issue is a logical bug. Also: Yes, I know I'm generating 4,000 Vector3's and then basically round tripping them. However, the purpose of this code is purely to learn how round tripping works between CPU and GPU in Unity.

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  • MPI Cluster Debugger launch integration in VS2010

    Let's assume that you have all the HPC bits installed and that you have existing MPI code (or you created a "Hello World" project using the MPI project template). Of course, you create a single MPI application and at runtime it will correspond to multiple processes (of the same app) launched on multiple nodes (i.e. machines) on the cluster. So how do you debug such a situation by simply hitting the familiar "F5" keystroke (i.e. Debug - Start Debugging)?WATCH IT INSTEAD OF READING ABOUT ITIf you can't bear to read through all the details below, just watch this 19-minute screencast explaining this VS2010 feature. Alternatively, or even additionally, keep on reading.REQUIREMENTWhen you debug an MPI application, you would want the copying of resources from your client machine (where Visual Studio is installed) to each compute node (where Windows HPC Server is installed) to take place automatically for you. 'Resources' in the previous sentence includes your application binary, plus any binary or data dependencies it may have, plus PDBs if needed, plus the debug CRT of the correct bitness, plus msvsmon for remote debugging to work. You would also want, after copying is complete, to have your app and msvsmon launched and attached so that you can hit breakpoints back in Visual Studio on your client machine. All these thing that you would want are delivered in VS2010.STEPS TO F51. In your MPI project where you have placed a breakpoint go to Project Properties - Configuration Properties - Debugging. Ensure the "Debugger to launch" combo box value is set to MPI Cluster Debugger.2. There are a whole bunch of properties here and typically you can ignore all of them except one: Run Environment. By default it is set to run 1 process on your local machine and if you change the number after that to, for example, 4 it will launch 4 processes of your app on your local machine.You want this to run on your cluster though, so go to the dropdown arrow at the end of the Run Environment cell and open it to expose the "Edit Hpc node" menu which opens the Node Selector dialog:In this dialog you can enter (or pick from a list) the cluster head node name and then the number of processes you want to execute on the cluster and then hit OK and… you are done.3. Press F5 and watch your breakpoint get hit (after giving it some time for copying, remote execution, attachment and symbol resolution to take place).GOING DEEPERIn the MPI Cluster Debugger project properties above, you can see many additional properties to the Run Environment. They are all optional, but you may want to understand them in order to fine tune your cluster debugging. Read all about each one of these on the MSDN page Configuration Properties for the MPI Cluster Debugger.In the Node Selector dialog above you can see more options than just the Head Node name and Number of Process to run. They should be self-explanatory but I also cover them in depth in my screencast showing you an example of why you would choose to schedule processes per core versus per node. You can also read about these options on MSDN as part of the page How to: Configure and Launch the MPI Cluster Debugger.To read through an example that touches on MPI project creation, project properties, node selector, and also usage of MPI with OpenMP plus MPI with PPL, read the MSDN page Walkthrough: Launching the MPI Cluster Debugger in Visual Studio 2010.Happy MPI debugging! Comments about this post welcome at the original blog.

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  • how to write the code for this program specially in mathematica? [closed]

    - by asd
    I implemented a solution to the problem below in Mathematica, but it takes a very long time (hours) to compute f of kis or the set B for large numbers. Somebody suggested that implementing this in C++ resulted in a solution in less than 10 minutes. Would C++ be a good language to learn to solve these problems, or can my Mathematica code be improved to fix the performance issues? I don't know anything about C or C++ and it should be difficult to start to learn this languages. I prefer to improve or write new code in mathematica. Problem Description Let $f$ be an arithmetic function and A={k1,k2,...,kn} are integers in increasing order. Now I want to start with k1 and compare f(ki) with f(k1). If f(ki)f(k1), put ki as k1. Now start with ki, and compare f(kj) with f(ki), for ji. If f(kj)f(ki), put kj as ki, and repeat this procedure. At the end we will have a sub sequence B={L1,...,Lm} of A by this property: f(L(i+1))f(L(i)), for any 1<=i<=m-1 For example, let f is the divisor function of integers. Here I put some part of my code and this is just a sample and the question in my program could be more larger than these: «««««««««««««««««««««««««««««««««««« f[n_] := DivisorSigma[0, n]; g[n_] := Product[Prime[i], {i, 1, PrimePi[n]}]; k1 = g[67757] g[353] g[59] g[19] g[11] g[7] g[5]^2 6^3 2^7; k2 = g[67757] g[353] g[59] g[19] g[11] g[7] g[5] 6^5 2^7; k3 = g[67757] g[359] g[53] g[19] g[11] g[7] g[5] 6^4 2^7; k4 = g[67759] g[349] g[53] g[19] g[11] g[7] g[5] 6^5 2^6; k5 = g[67757] g[359] g[53] g[19] g[11] g[7] g[5] 6^4 2^8; k6 = g[67759] g[349] g[53] g[19] g[11] g[7] g[5]^2 6^3 2^7; k7 = g[67757] g[359] g[53] g[19] g[11] g[7] g[5] 6^5 2^6; k8 = g[67757] g[359] g[53] g[19] g[11] g[7] g[5] 6^4 2^9; k9 = g[67757] g[359] g[53] g[19] g[11] g[7] g[5]^2 6^3 2^7; k10 = g[67757] g[359] g[53] g[19] g[11] g[7] g[5] 6^5 2^7; k11 = g[67759] g[349] g[53] g[19] g[11] g[7] g[5]^2 6^4 2^6; k12 = g[67757] g[359] g[53] g[19] g[11] g[7] g[5]^2 6^3 2^8; k13 = g[67757] g[359] g[53] g[19] g[11] g[7] g[5]^2 6^4 2^6; k14 = g[67757] g[359] g[53] g[19] g[11] g[7] g[5]^2 6^3 2^9; k15 = g[67757] g[359] g[53] g[19] g[11] g[7] g[5]^2 6^4 2^7; k16 = g[67757] g[359] g[53] g[23] g[11] g[7] g[5] 6^4 2^8; k17 = g[67757] g[359] g[59] g[19] g[11] g[7] g[5] 6^4 2^7; k18 = g[67757] g[359] g[53] g[23] g[11] g[7] g[5] 6^4 2^9; k19 = g[67759] g[353] g[53] g[19] g[11] g[7] g[5] 6^4 2^6; k20 = g[67763] g[347] g[53] g[19] g[11] g[7] g[5] 6^4 2^7; k = Table[k1, k2, k3, k4, k5, k6, k7, k8, k9, k10, k11, k12, k13, k14, k15, k16, k17, k18, k19, k20]; i = 1; count = 0; For[j = i, j <= 20, j++, If[f[k[[j]]] - f[k[[i]]] > 0, i = j; Print["k",i]; count = count + 1]]; Print["count= ", count] ««««««««««««««««««««««««««««««««««««

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  • Arcball Problems with UDK

    - by opdude
    I'm trying to re-create an arcball example from a Nehe, where an object can be rotated in a more realistic way while floating in the air (in my game the object is attached to the player at a distance like for example the Physics Gun) however I'm having trouble getting this to work with UDK. I have created an LGArcBall which follows the example from Nehe and I've compared outputs from this with the example code. I think where my problem lies is what I do to the Quaternion that is returned from the LGArcBall. Currently I am taking the returned Quaternion converting it to a rotation matrix. Getting the product of the last rotation (set when the object is first clicked) and then returning that into a Rotator and setting that to the objects rotation. If you could point me in the right direction that would be great, my code can be found below. class LGArcBall extends Object; var Quat StartRotation; var Vector StartVector; var float AdjustWidth, AdjustHeight, Epsilon; function SetBounds(float NewWidth, float NewHeight) { AdjustWidth = 1.0f / ((NewWidth - 1.0f) * 0.5f); AdjustHeight = 1.0f / ((NewHeight - 1.0f) * 0.5f); } function StartDrag(Vector2D startPoint, Quat rotation) { StartVector = MapToSphere(startPoint); } function Quat Update(Vector2D currentPoint) { local Vector currentVector, perp; local Quat newRot; //Map the new point to the sphere currentVector = MapToSphere(currentPoint); //Compute the vector perpendicular to the start and current perp = startVector cross currentVector; //Make sure our length is larger than Epsilon if (VSize(perp) > Epsilon) { //Return the perpendicular vector as the transform newRot.X = perp.X; newRot.Y = perp.Y; newRot.Z = perp.Z; //In the quaternion values, w is cosine (theta / 2), where //theta is the rotation angle newRot.W = startVector dot currentVector; } else { //The two vectors coincide, so return an identity transform newRot.X = 0.0f; newRot.Y = 0.0f; newRot.Z = 0.0f; newRot.W = 0.0f; } return newRot; } function Vector MapToSphere(Vector2D point) { local float x, y, length, norm; local Vector result; //Transform the mouse coords to [-1..1] //and inverse the Y coord x = (point.X * AdjustWidth) - 1.0f; y = 1.0f - (point.Y * AdjustHeight); length = (x * x) + (y * y); //If the point is mapped outside of the sphere //( length > radius squared) if (length > 1.0f) { norm = 1.0f / Sqrt(length); //Return the "normalized" vector, a point on the sphere result.X = x * norm; result.Y = y * norm; result.Z = 0.0f; } else //It's inside of the sphere { //Return a vector to the point mapped inside the sphere //sqrt(radius squared - length) result.X = x; result.Y = y; result.Z = Sqrt(1.0f - length); } return result; } DefaultProperties { Epsilon = 0.000001f } I'm then attempting to rotate that object when the mouse is dragged, with the following update code in my PlayerController. //Get Mouse Position MousePosition.X = LGMouseInterfacePlayerInput(PlayerInput).MousePosition.X; MousePosition.Y = LGMouseInterfacePlayerInput(PlayerInput).MousePosition.Y; newQuat = ArcBall.Update(MousePosition); rotMatrix = MakeRotationMatrix(QuatToRotator(newQuat)); rotMatrix = rotMatrix * LastRot; LGMoveableActor(movingPawn.CurrentUseableObject).SetPhysics(EPhysics.PHYS_Rotating); LGMoveableActor(movingPawn.CurrentUseableObject).SetRotation(MatrixGetRotator(rotMatrix));

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  • Cloud Computing Pricing - It's like a Hotel

    - by BuckWoody
    I normally don't go into the economics or pricing side of Distributed Computing, but I've had a few friends that have been surprised by a bill lately and I wanted to quickly address at least one aspect of it. Most folks are used to buying software and owning it outright - like buying a car. We pay a lot for the car, and then we use it whenever we want. We think of the "cloud" services as a taxi - we'll just pay for the ride we take an no more. But it's not quite like that. It's actually more like a hotel. When you subscribe to Azure using a free offering like the MSDN subscription, you don't have to pay anything for the service. But when you create an instance of a Web or Compute Role, Storage, that sort of thing, you can think of the idea of checking into a hotel room. You get the key, you pay for the room. For Azure, using bandwidth, CPU and so on is billed just like it states in the Azure Portal. so in effect there is a cost for the service and then a cost to use it, like water or power or any other utility. Where this bit some folks is that they created an instance, played around with it, and then left it running. No one was using it, no one was on - so they thought they wouldn't be charged. But they were. It wasn't much, but it was a surprise.They had the hotel room key, but they weren't in the room, so to speak. To add to their frustration, they had to talk to someone on the phone to cancel the account. I understand the frustration. Although we have all this spelled out in the sign up area, not everyone has the time to read through all that. I get that. So why not make this easier? As an explanation, we bill for that time because the instance is still running, and we have to tie up resources to be available the second you want them, and that costs money. As far as being able to cancel from the portal, that's also something that needs to be clearer. You may not be aware that you can spin up instances using code - and so cancelling from the Portal would allow you to do the same thing. Since a mistake in code could erase all of your instances and the account, we make you call to make sure you're you and you really want to take it down. Not a perfect system by any means, but we'll evolve this as time goes on. For now, I wanted to make sure you're aware of what you should do. By the way, you don't have to cancel your whole account not to be billed. Just delete the instance from the portal and you won't be charged. You don't have to call anyone for that. And just FYI - you can download the SDK for Azure and never even hit the online version at all for learning and playing around. No sign-up, no credit card, PO, nothing like that. In fact, that's how I demo Azure all the time. Everything runs right on your laptop in an emulated environment.  

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  • About the K computer

    - by nospam(at)example.com (Joerg Moellenkamp)
    Okay ? after getting yet another mail because of the new #1 on the Top500 list, I want to add some comments from my side: Yes, the system is using SPARC processor. And that is great news for a SPARC fan like me. It is using the SPARC VIIIfx processor from Fujitsu clocked at 2 GHz. No, it isn't the only one. Most people are saying there are two in the Top500 list using SPARC (#77 JAXA and #1 K) but in fact there are three. The Tianhe-1 (#2 on the Top500 list) super computer contains 2048 Galaxy "FT-1000" 1 GHz 8-core processors. Don't know it? The FeiTeng-1000 ? this proc is a 8 core, 8 threads per core, 1 ghz processor made in China. And it's SPARC based. By the way ? this sounds really familiar to me ? perhaps the people just took the opensourced UltraSPARC-T2 design, because some of the parameters sound just to similar. However it looks like that Tianhe-1 is using the SPARCs as input nodes and not as compute notes. No, I don't see it as the next M-series processor. Simple reason: You can't create SMP systems out of them ? it simply hasn't the functionality to do so. Even when there are multiple CPUs on a single board, they are not connected like an SMP/NUMA machine to a shared memory machine ? they are connected with the cluster interconnect (in this case the Tofu interconnect) and work like a large cluster. Yes, it has a lot of oomph in Linpack ? however I assume a lot came from the extensions to the SPARCv9 standard. No, Linpack has no relevance for any commercial workload ? Linpack is such a special load, that even some HPC people are arguing that it isn't really a good benchmark for HPC. It's embarrassingly parallel, it can work with relatively small interconnects compared to the interconnects in SMP systems (however we get in spheres SMP interconnects where a few years ago). Amdahl isn't hitting that hard when running Linpack. Yes, it's a good move to use SPARC. At some time in the last 10 years, there was an interesting twist in perception: SPARC was considered as proprietary architecture and x86 was the open architecture. However it's vice versa ? try to create a x86 clone and you have a lot of intellectual property problems, create a SPARC clone and you have to spend 100 bucks or so to get the specification from the SPARC Foundation and develop your own SPARC processor. Fujitsu is doing this for a long time now. So they had their own processor, their own know-how. So why was SPARC a good choice? Well ? essentially Fujitsu can do what they want with their core as it is their core, for example adding the extensions to the SPARCv9 chipset ? getting Intel to create extensions to x86 to help you with your product is a little bit harder. So Fujitsu could do they needed to do with their processor in order to create such a supercomputer. No, the K is really using no FPGA or GPU as accelerators. The K is really using the CPU at doing this job. Yes, it has a significantly enhanced FPU capable to execute 8 instructions in parallel. No, it doesn't run Solaris. Yes, it uses Linux. No, it doesn't hurt me ... as my colleague Roland Rambau (he knows a lot about HPC) said once to me ... it doesn't matter which OS is staying out of the way of the workload in HPC.

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