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  • Is your team is a high-performing team?

    As a child I can remember looking out of the car window as my father drove along the Interstate in Florida while seeing prisoners wearing bright orange jump suits and prison guards keeping a watchful eye on them. The prisoners were taking part in a prison road gang. These road gangs were formed to help the state maintain the state highway infrastructure. The prisoner’s primary responsibilities are to pick up trash and debris from the roadway. This is a prime example of a work group or working group used by most prison systems in the United States. Work groups or working groups can be defined as a collection of individuals or entities working together to achieve a specific goal or accomplish a specific set of tasks. Typically these groups are only established for a short period of time and are dissolved once the desired outcome has been achieved. More often than not group members usually feel as though they are expendable to the group and some even dread that they are even in the group. "A team is a small number of people with complementary skills who are committed to a common purpose, performance goals, and approach for which they are mutually accountable." (Katzenbach and Smith, 1993) So how do you determine that a team is a high-performing team?  This can be determined by three base line criteria that include: consistently high quality output, the promotion of personal growth and well being of all team members, and most importantly the ability to learn and grow as a unit. Initially, a team can successfully create high-performing output without meeting all three criteria, however this will erode over time because team members will feel detached from the group or that they are not growing then the quality of the output will decline. High performing teams are similar to work groups because they both utilize a collection of individuals or entities to accomplish tasks. What distinguish a high-performing team from a work group are its characteristics. High-performing teams contain five core characteristics. These characteristics are what separate a group from a team. The five characteristics of a high-performing team include: Purpose, Performance Measures, People with Tasks and Relationship Skills, Process, and Preparation and Practice. A high-performing team is much more than a work group, and typically has a life cycle that can vary from team to team. The standard team lifecycle consists of five states and is comparable to a human life cycle. The five states of a high-performing team lifecycle include: Formulating, Storming, Normalizing, Performing, and Adjourning. The Formulating State of a team is first realized when the team members are first defined and roles are assigned to all members. This initial stage is very important because it can set the tone for the team and can ultimately determine its success or failure. In addition, this stage requires the team to have a strong leader because team members are normally unclear about specific roles, specific obstacles and goals that my lay ahead of them.  Finally, this stage is where most team members initially meet one another prior to working as a team unless the team members already know each other. The Storming State normally arrives directly after the formulation of a new team because there are still a lot of unknowns amongst the newly formed assembly. As a general rule most of the parties involved in the team are still getting used to the workload, pace of work, deadlines and the validity of various tasks that need to be performed by the group.  In this state everything is questioned because there are so many unknowns. Items commonly questioned include the credentials of others on the team, the actual validity of a project, and the leadership abilities of the team leader.  This can be exemplified by looking at the interactions between animals when they first meet.  If we look at a scenario where two people are walking directly toward each other with their dogs. The dogs will automatically enter the Storming State because they do not know the other dog. Typically in this situation, they attempt to define which is more dominating via play or fighting depending on how the dogs interact with each other. Once dominance has been defined and accepted by both dogs then they will either want to play or leave depending on how the dogs interacted and other environmental variables. Once the Storming State has been realized then the Normalizing State takes over. This state is entered by a team once all the questions of the Storming State have been answered and the team has been tested by a few tasks or projects.  Typically, participants in the team are filled with energy, and comradery, and a strong alliance with team goals and objectives.  A high school football team is a perfect example of the Normalizing State when they start their season.  The player positions have been assigned, the depth chart has been filled and everyone is focused on winning each game. All of the players encourage and expect each other to perform at the best of their abilities and are united by competition from other teams. The Performing State is achieved by a team when its history, working habits, and culture solidify the team as one working unit. In this state team members can anticipate specific behaviors, attitudes, reactions, and challenges are seen as opportunities and not problems. Additionally, each team member knows their role in the team’s success, and the roles of others. This is the most productive state of a group and is where all the time invested working together really pays off. If you look at an Olympic figure skating team skate you can easily see how the time spent working together benefits their performance. They skate as one unit even though it is comprised of two skaters. Each skater has their routine completely memorized as well as their partners. This allows them to anticipate each other’s moves on the ice makes their skating look effortless. The final state of a team is the Adjourning State. This state is where accomplishments by the team and each individual team member are recognized. Additionally, this state also allows for reflection of the interactions between team members, work accomplished and challenges that were faced. Finally, the team celebrates the challenges they have faced and overcome as a unit. Currently in the workplace teams are divided into two different types: Co-located and Distributed Teams. Co-located teams defined as the traditional group of people working together in an office, according to Andy Singleton of Assembla. This traditional type of a team has dominated business in the past due to inadequate technology, which forced workers to primarily interact with one another via face to face meetings.  Team meetings are primarily lead by the person with the highest status in the company. Having personally, participated in meetings of this type, usually a select few of the team members dominate the flow of communication which reduces the input of others in group discussions. Since discussions are dominated by a select few individuals the discussions and group discussion are skewed in favor of the individuals who communicate the most in meetings. In addition, Team members might not give their full opinions on a topic of discussion in part not to offend or create controversy amongst the team and can alter decision made in meetings towards those of the opinions of the dominating team members. Distributed teams are by definition spread across an area or subdivided into separate sections. That is exactly what distributed teams when compared to a more traditional team. It is common place for distributed teams to have team members across town, in the next state, across the country and even with the advances in technology over the last 20 year across the world. These teams allow for more diversity compared to the other type of teams because they allow for more flexibility regarding location. A team could consist of a 30 year old male Italian project manager from New York, a 50 year old female Hispanic from California and a collection of programmers from India because technology allows them to communicate as if they were standing next to one another.  In addition, distributed team members consult with more team members prior to making decisions compared to traditional teams, and take longer to come to decisions due to the changes in time zones and cultural events. However, team members feel more empowered to speak out when they do not agree with the team and to notify others of potential issues regarding the work that the team is doing. Virtual teams which are a subset of the distributed team type is changing organizational strategies due to the fact that a team can now in essence be working 24 hrs a day because of utilizing employees in various time zones and locations.  A primary example of this is with customer services departments, a company can have multiple call centers spread across multiple time zones allowing them to appear to be open 24 hours a day while all a employees work from 9AM to 5 PM every day. Virtual teams also allow human resources departments to go after the best talent for the company regardless of where the potential employee works because they will be a part of a virtual team all that is need is the proper technology to be setup to allow everyone to communicate. In addition to allowing employees to work from home, the company can save space and resources by not having to provide a desk for every team member. In fact, those team members that randomly come into the office can actually share one desk amongst multiple people. This is definitely a cost cutting plus given the current state of the economy. One thing that can turn a team into a high-performing team is leadership. High-performing team leaders need to focus on investing in ongoing personal development, provide team members with direction, structure, and resources needed to accomplish their work, make the right interventions at the right time, and help the team manage boundaries between the team and various external parties involved in the teams work. A team leader needs to invest in ongoing personal development in order to effectively manage their team. People have said that attitude is everything; this is very true about leaders and leadership. A team takes on the attitudes and behaviors of its leaders. This can potentially harm the team and the team’s output. Leaders must concentrate on self-awareness, and understanding their team’s group dynamics to fully understand how to lead them. In addition, always learning new leadership techniques from other effective leaders is also very beneficial. Providing team members with direction, structure, and resources that they need to accomplish their work collectively sounds easy, but it is not.  Leaders need to be able to effectively communicate with their team on how their work helps the company reach for its organizational vision. Conversely, the leader needs to allow his team to work autonomously within specific guidelines to turn the company’s vision into a reality.  This being said the team must be appropriately staffed according to the size of the team’s tasks and their complexity. These tasks should be clear, and be meaningful to the company’s objectives and allow for feedback to be exchanged with the leader and the team member and the leader and upper management. Now if the team is properly staffed, and has a clear and full understanding of what is to be done; the company also must supply the workers with the proper tools to achieve the tasks that they are asked to do. No one should be asked to dig a hole without being given a shovel.  Finally, leaders must reward their team members for accomplishments that they achieve. Awards could range from just a simple congratulatory email, a party to close the completion of a large project, or other monetary rewards. Managing boundaries is very important for team leaders because it can alter attitudes of team members and can add undue stress to the team which will force them to loose focus on the tasks at hand for the group. Team leaders should promote communication between team members so that burdens are shared amongst the team and solutions can be derived from hearing the opinions of multiple sources. This also reinforces team camaraderie and working as a unit. Team leaders must manage the type and timing of interventions as to not create an even bigger mess within the team. Poorly timed interventions can really deflate team members and make them question themselves. This could really increase further and undue interventions by the team leader. Typically, the best time for interventions is when the team is just starting to form so that all unproductive behaviors are removed from the team and that it can retain focus on its agenda. If an intervention is effectively executed the team will feel energized about the work that they are doing, promote communication and interaction amongst the group and improve moral overall. High-performing teams are very import to organizations because they consistently produce high quality output and develop a collective purpose for their work. This drive to succeed allows team members to utilize specific talents allowing for growth in these areas.  In addition, these team members usually take on a sense of ownership with their projects and feel that the other team members are irreplaceable. References: http://blog.assembla.com/assemblablog/tabid/12618/bid/3127/Three-ways-to-organize-your-team-co-located-outsourced-or-global.aspx Katzenbach, J.R. & Smith, D.K. (1993). The Wisdom of Teams: Creating the High-performance Organization. Boston: Harvard Business School.

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  • Gradual memory leak in loop over contents of QTMovie

    - by Benji XVI
    I have a simple foundation tool that exports every frame of a movie as a .tiff file. Here is the relevant code: NSString* movieLoc = [NSString stringWithCString:argv[1]]; QTMovie *sourceMovie = [QTMovie movieWithFile:movieLoc error:nil]; int i=0; while (QTTimeCompare([sourceMovie currentTime], [sourceMovie duration]) != NSOrderedSame) { // save image of movie to disk NSAutoreleasePool *arp = [[NSAutoreleasePool alloc] init]; NSString *filePath = [NSString stringWithFormat:@"/somelocation_%d.tiff", i++]; NSData *currentImageData = [[sourceMovie currentFrameImage] TIFFRepresentation]; [currentImageData writeToFile:filePath atomically:NO]; NSLog(@"%@", filePath); [sourceMovie stepForward]; [arp release]; } [pool drain]; return 0; As you can see, in order to prevent very large memory buildups with the various transparently-autoreleased variables in the loop, we create, and flush, an autoreleasepool with every run through the loop. However, over the course of stepping through a movie, the amount of memory used by the program still gradually increases. Instruments is not detecting any memory leaks per se, but the object trace shows certain General Data blocks to be increasing in size. [Edited out reference to slowdown as it doesn't seem to be as much of a problem as I thought.] Edit: let's knock out some parts of the code inside the loop & see what we find out... Test 1 while (banana) { NSAutoreleasePool *arp = [[NSAutoreleasePool alloc] init]; NSString *filePath = [NSString stringWithFormat:@"/somelocation_%d.tiff", i++]; NSLog(@"%@", filePath); [sourceMovie stepForward]; [arp release]; } Here we simply loop over the whole movie, creating the filename and logging it. Memory characteristics: remains at 15MB usage for the duration. Test 2 while (banana) { NSAutoreleasePool *arp = [[NSAutoreleasePool alloc] init]; NSImage *image = [sourceMovie currentFrameImage]; [sourceMovie stepForward]; [arp release]; } Here we add back in the creation of the NSImage from the current frame. Memory characteristics: gradually increasing memory usage. RSIZE is at 60MB by frame 200; 75MB by f300. Test 3 while (banana) { NSAutoreleasePool *arp = [[NSAutoreleasePool alloc] init]; NSImage *image = [sourceMovie currentFrameImage]; NSData *imageData = [image TIFFRepresentation]; [sourceMovie stepForward]; [arp release]; } We've added back in the creation of an NSData object from the NSImage. Memory characteristics: Memory usage is again increasing: 62MB at f200; 75MB at f300. In other words, largely identical. It looks like a memory leak in the underlying system QTMovie uses to do currentFrameImage, to me.

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  • From Binary to Data Structures

    - by Cédric Menzi
    Table of Contents Introduction PE file format and COFF header COFF file header BaseCoffReader Byte4ByteCoffReader UnsafeCoffReader ManagedCoffReader Conclusion History This article is also available on CodeProject Introduction Sometimes, you want to parse well-formed binary data and bring it into your objects to do some dirty stuff with it. In the Windows world most data structures are stored in special binary format. Either we call a WinApi function or we want to read from special files like images, spool files, executables or may be the previously announced Outlook Personal Folders File. Most specifications for these files can be found on the MSDN Libarary: Open Specification In my example, we are going to get the COFF (Common Object File Format) file header from a PE (Portable Executable). The exact specification can be found here: PECOFF PE file format and COFF header Before we start we need to know how this file is formatted. The following figure shows an overview of the Microsoft PE executable format. Source: Microsoft Our goal is to get the PE header. As we can see, the image starts with a MS-DOS 2.0 header with is not important for us. From the documentation we can read "...After the MS DOS stub, at the file offset specified at offset 0x3c, is a 4-byte...". With this information we know our reader has to jump to location 0x3c and read the offset to the signature. The signature is always 4 bytes that ensures that the image is a PE file. The signature is: PE\0\0. To prove this we first seek to the offset 0x3c, read if the file consist the signature. So we need to declare some constants, because we do not want magic numbers.   private const int PeSignatureOffsetLocation = 0x3c; private const int PeSignatureSize = 4; private const string PeSignatureContent = "PE";   Then a method for moving the reader to the correct location to read the offset of signature. With this method we always move the underlining Stream of the BinaryReader to the start location of the PE signature.   private void SeekToPeSignature(BinaryReader br) { // seek to the offset for the PE signagure br.BaseStream.Seek(PeSignatureOffsetLocation, SeekOrigin.Begin); // read the offset int offsetToPeSig = br.ReadInt32(); // seek to the start of the PE signature br.BaseStream.Seek(offsetToPeSig, SeekOrigin.Begin); }   Now, we can check if it is a valid PE image by reading of the next 4 byte contains the content PE.   private bool IsValidPeSignature(BinaryReader br) { // read 4 bytes to get the PE signature byte[] peSigBytes = br.ReadBytes(PeSignatureSize); // convert it to a string and trim \0 at the end of the content string peContent = Encoding.Default.GetString(peSigBytes).TrimEnd('\0'); // check if PE is in the content return peContent.Equals(PeSignatureContent); }   With this basic functionality we have a good base reader class to try the different methods of parsing the COFF file header. COFF file header The COFF header has the following structure: Offset Size Field 0 2 Machine 2 2 NumberOfSections 4 4 TimeDateStamp 8 4 PointerToSymbolTable 12 4 NumberOfSymbols 16 2 SizeOfOptionalHeader 18 2 Characteristics If we translate this table to code, we get something like this:   [StructLayout(LayoutKind.Sequential, CharSet = CharSet.Unicode)] public struct CoffHeader { public MachineType Machine; public ushort NumberOfSections; public uint TimeDateStamp; public uint PointerToSymbolTable; public uint NumberOfSymbols; public ushort SizeOfOptionalHeader; public Characteristic Characteristics; } BaseCoffReader All readers do the same thing, so we go to the patterns library in our head and see that Strategy pattern or Template method pattern is sticked out in the bookshelf. I have decided to take the template method pattern in this case, because the Parse() should handle the IO for all implementations and the concrete parsing should done in its derived classes.   public CoffHeader Parse() { using (var br = new BinaryReader(File.Open(_fileName, FileMode.Open, FileAccess.Read, FileShare.Read))) { SeekToPeSignature(br); if (!IsValidPeSignature(br)) { throw new BadImageFormatException(); } return ParseInternal(br); } } protected abstract CoffHeader ParseInternal(BinaryReader br);   First we open the BinaryReader, seek to the PE signature then we check if it contains a valid PE signature and rest is done by the derived implementations. Byte4ByteCoffReader The first solution is using the BinaryReader. It is the general way to get the data. We only need to know which order, which data-type and its size. If we read byte for byte we could comment out the first line in the CoffHeader structure, because we have control about the order of the member assignment.   protected override CoffHeader ParseInternal(BinaryReader br) { CoffHeader coff = new CoffHeader(); coff.Machine = (MachineType)br.ReadInt16(); coff.NumberOfSections = (ushort)br.ReadInt16(); coff.TimeDateStamp = br.ReadUInt32(); coff.PointerToSymbolTable = br.ReadUInt32(); coff.NumberOfSymbols = br.ReadUInt32(); coff.SizeOfOptionalHeader = (ushort)br.ReadInt16(); coff.Characteristics = (Characteristic)br.ReadInt16(); return coff; }   If the structure is as short as the COFF header here and the specification will never changed, there is probably no reason to change the strategy. But if a data-type will be changed, a new member will be added or ordering of member will be changed the maintenance costs of this method are very high. UnsafeCoffReader Another way to bring the data into this structure is using a "magically" unsafe trick. As above, we know the layout and order of the data structure. Now, we need the StructLayout attribute, because we have to ensure that the .NET Runtime allocates the structure in the same order as it is specified in the source code. We also need to enable "Allow unsafe code (/unsafe)" in the project's build properties. Then we need to add the following constructor to the CoffHeader structure.   [StructLayout(LayoutKind.Sequential, CharSet = CharSet.Unicode)] public struct CoffHeader { public CoffHeader(byte[] data) { unsafe { fixed (byte* packet = &data[0]) { this = *(CoffHeader*)packet; } } } }   The "magic" trick is in the statement: this = *(CoffHeader*)packet;. What happens here? We have a fixed size of data somewhere in the memory and because a struct in C# is a value-type, the assignment operator = copies the whole data of the structure and not only the reference. To fill the structure with data, we need to pass the data as bytes into the CoffHeader structure. This can be achieved by reading the exact size of the structure from the PE file.   protected override CoffHeader ParseInternal(BinaryReader br) { return new CoffHeader(br.ReadBytes(Marshal.SizeOf(typeof(CoffHeader)))); }   This solution is the fastest way to parse the data and bring it into the structure, but it is unsafe and it could introduce some security and stability risks. ManagedCoffReader In this solution we are using the same approach of the structure assignment as above. But we need to replace the unsafe part in the constructor with the following managed part:   [StructLayout(LayoutKind.Sequential, CharSet = CharSet.Unicode)] public struct CoffHeader { public CoffHeader(byte[] data) { IntPtr coffPtr = IntPtr.Zero; try { int size = Marshal.SizeOf(typeof(CoffHeader)); coffPtr = Marshal.AllocHGlobal(size); Marshal.Copy(data, 0, coffPtr, size); this = (CoffHeader)Marshal.PtrToStructure(coffPtr, typeof(CoffHeader)); } finally { Marshal.FreeHGlobal(coffPtr); } } }     Conclusion We saw that we can parse well-formed binary data to our data structures using different approaches. The first is probably the clearest way, because we know each member and its size and ordering and we have control about the reading the data for each member. But if add member or the structure is going change by some reason, we need to change the reader. The two other solutions use the approach of the structure assignment. In the unsafe implementation we need to compile the project with the /unsafe option. We increase the performance, but we get some security risks.

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  • How fast are my services? Comparing basicHttpBinding and ws2007HttpBinding using the SO-Aware Test Workbench

    - by gsusx
    When working on real world WCF solutions, we become pretty aware of the performance implications of the binding and behavior configuration of WCF services. However, whether it’s a known fact the different binding and behavior configurations have direct reflections on the performance of WCF services, developers often struggle to figure out the real performance behavior of the services. We can attribute this to the lack of tools for correctly testing the performance characteristics of WCF services...(read more)

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  • Best Practices for Building a Virtualized SPARC Computing Environment

    - by Scott Elvington
    Normal 0 false false false EN-US X-NONE X-NONE /* 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 just published Best Practices for Building a Virtualized SPARC Computing Environment, a white paper that provides guidance on the complete hardware and software stack for deploying and managing your physical and virtual SPARC infrastructure. The solution is based on Oracle SPARC T4 servers, Oracle Solaris 11 with Oracle VM for SPARC 2.2, Sun ZFS storage appliances, Sun 10GbE 72 port switches and Oracle Enterprise Manager Ops Center 12c. The paper emphasizes the value and importance of planning the resources (compute, network and storage) that will comprise the virtualized environment to achieve the desired capacity, performance and availability characteristics. The document also details numerous operational best practices that will help you deliver on those characteristics with unique capabilities provided by Enterprise Manager Ops Center including policy-based guest placement, pool resource balancing and automated guest recovery in the event of server failure. Plenty of references to supplementary documentation are included to help point you to additional resources. Whether you’re building the first stages of your private cloud or a general-purpose virtualized SPARC computing environment, these documented best practices will help ensure success. Please join Phil Bullinger and Steve Wilson from Oracle to learn more about breakthrough efficiency in private cloud infrastructure and how SPARC based virtualization can help you get started on your cloud journey. Stay Connected: Twitter |  Face book |  You Tube |  Linked in |  Newsletter

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  • Introducing SQL Server 2008 and 2008 R2 Integration Services

    The latest release of SSIS strengthens its position as one of the primary foundations of Business Intelligence, delivering a powerful framework for solutions that combine data from disparate sources, facilitating its analysis and reporting. Join Marcin Policht as he reviews its general characteristics.

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  • Bin packing part 6: Further improvements

    - by Hugo Kornelis
    In part 5 of my series on the bin packing problem, I presented a method that sits somewhere in between the true row-by-row iterative characteristics of the first three parts and the truly set-based approach of the fourth part. I did use iteration, but each pass through the loop would use a set-based statement to process a lot of rows at once. Since that statement is fairly complex, I am sure that a single execution of it is far from cheap – but the algorithm used is efficient enough that the entire...(read more)

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  • System blacks out when resuming on opening lid

    - by Ashfaq
    It is happening now and then but frequently these days. My system E420 Lenovo Thinkpad running 12.04 LTS blacks out and doesn't respond when woke up from sleep by opening the lid. I then have to forcibly press the Start button and restart the entire system which is creating a headache for me. Please suggest a way to overcome this problem. Main characteristics leading to this that I have noticed are: When a video is paused before I suspend the system When Eclipse or pgAdmin is running before suspending the system

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  • Are there deprecated practices for multithread and multiprocessor programming that I should no longer use?

    - by DeveloperDon
    In the early days of FORTRAN and BASIC, essentially all programs were written with GOTO statements. The result was spaghetti code and the solution was structured programming. Similarly, pointers can have difficult to control characteristics in our programs. C++ started with plenty of pointers, but use of references are recommended. Libraries like STL can reduce some of our dependency. There are also idioms to create smart pointers that have better characteristics, and some version of C++ permit references and managed code. Programming practices like inheritance and polymorphism use a lot of pointers behind the scenes (just as for, while, do structured programming generates code filled with branch instructions). Languages like Java eliminate pointers and use garbage collection to manage dynamically allocated data instead of depending on programmers to match all their new and delete statements. In my reading, I have seen examples of multi-process and multi-thread programming that don't seem to use semaphores. Do they use the same thing with different names or do they have new ways of structuring protection of resources from concurrent use? For example, a specific example of a system for multithread programming with multicore processors is OpenMP. It represents a critical region as follows, without the use of semaphores, which seem not to be included in the environment. th_id = omp_get_thread_num(); #pragma omp critical { cout << "Hello World from thread " << th_id << '\n'; } This example is an excerpt from: http://en.wikipedia.org/wiki/OpenMP Alternatively, similar protection of threads from each other using semaphores with functions wait() and signal() might look like this: wait(sem); th_id = get_thread_num(); cout << "Hello World from thread " << th_id << '\n'; signal(sem); In this example, things are pretty simple, and just a simple review is enough to show the wait() and signal() calls are matched and even with a lot of concurrency, thread safety is provided. But other algorithms are more complicated and use multiple semaphores (both binary and counting) spread across multiple functions with complex conditions that can be called by many threads. The consequences of creating deadlock or failing to make things thread safe can be hard to manage. Do these systems like OpenMP eliminate the problems with semaphores? Do they move the problem somewhere else? How do I transform my favorite semaphore using algorithm to not use semaphores anymore?

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  • Good GUI for OpenGL

    - by Cristina
    I am starting to learn OpenGL with FreeGLUT using the Superbible and the knowledge i have from my elementary graphics to brush up on my skills. To get more from this experience i want to integrate a GUI to overwrite the one FreeGLUT uses, now my question is this: is this thing possible and what library should i use? Some characteristics for the library: Open source Multi-platform (Linux and Windows) C/C++ If you have any other recommendations please feel free to post them along with your answers for my problem.

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  • Is there a canonical resource on multi-tenancy web applications using ruby + rails

    - by AlexC
    Is there a canonical resource on multi-tenancy web applications using ruby + rails. There are a number of ways to develop rails apps using cloud capabilities with real elastic properties but there seems to be a lack of clarity with how to achieve multitenancy, specifically at the model / data level. Is there a canonical resource on options to developing multitenancy rails applications with the required characteristics of data seperation, security, concurrency and contention required by an enterprise level cloud application.

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  • What do you code first to learn a new language, library, or framework?

    - by Griffin
    Every language, framework, and library has its own syntax, quirks, and pitfalls. What Program, Game, etc. do you code in order to learn these unique characteristics? How do you decide on what previous programming experience is applicable? I'd imagine that the task would have to be complicated enough to force you to use applicable programming techniques and idioms, but simple enough that it wouldn't take a ton of time.

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  • Do programmers have a higher IQ? [closed]

    - by Laurent Pireyn
    Do programmers have a higher intellectual quotient than the average 100? Has anybody conducted studies on that topic? Don't get me wrong! I consider IQ as a limited measure that only evaluates the analytical part of one's intelligence. Furthermore, I think that intelligence is only one among many characteristics, and that it should not be used to judge or discriminate people. My question should be read in that context.

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  • 24 Hours of PASS next week, pre-con preview style

    - by drsql
    I will be doing my Characteristics of a Great Relational Database , which is a session that I haven’t done since last PASS. When I was asked about doing this Summit Preview version of 24 hours of PASS, I decided that I would do this session, largely because it is kind of light and fun, but also because it is either going to be the basis of the end section of my pre-con at the summit or it is going to be the section of the pre-con we don’t get to because we are so involved in working out designs that...(read more)

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  • Recording Available: Oracle ETPM Performance Forum: "Scalability", Wednesday March 21st, at 1pm EST - 4:30pm EST

    - by Rick Finley
    Attached is the recording URL last months Oracle ETPM Performance forum meeting, from Wednesday, March 21st, at 1pm EST to 2:30pm EST.  The topic was “Scalability".  The topic focuses on an overview of important Scalability concetps, scalability testing and troubleshooting, and ETPM scalability characteristics we have seen in our benchmark testing.   Meeting Recording Playback URL:  https://oracletalk.webex.com/oracletalk/ldr.php?AT=pb&SP=MC&rID=67420077&rKey=73798b44e06240dd 

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  • Organization &amp; Architecture UNISA Studies &ndash; Chap 4

    - by MarkPearl
    Learning Outcomes Explain the characteristics of memory systems Describe the memory hierarchy Discuss cache memory principles Discuss issues relevant to cache design Describe the cache organization of the Pentium Computer Memory Systems There are key characteristics of memory… Location – internal or external Capacity – expressed in terms of bytes Unit of Transfer – the number of bits read out of or written into memory at a time Access Method – sequential, direct, random or associative From a users perspective the two most important characteristics of memory are… Capacity Performance – access time, memory cycle time, transfer rate The trade off for memory happens along three axis… Faster access time, greater cost per bit Greater capacity, smaller cost per bit Greater capacity, slower access time This leads to people using a tiered approach in their use of memory   As one goes down the hierarchy, the following occurs… Decreasing cost per bit Increasing capacity Increasing access time Decreasing frequency of access of the memory by the processor The use of two levels of memory to reduce average access time works in principle, but only if conditions 1 to 4 apply. A variety of technologies exist that allow us to accomplish this. Thus it is possible to organize data across the hierarchy such that the percentage of accesses to each successively lower level is substantially less than that of the level above. A portion of main memory can be used as a buffer to hold data temporarily that is to be read out to disk. This is sometimes referred to as a disk cache and improves performance in two ways… Disk writes are clustered. Instead of many small transfers of data, we have a few large transfers of data. This improves disk performance and minimizes processor involvement. Some data designed for write-out may be referenced by a program before the next dump to disk. In that case the data is retrieved rapidly from the software cache rather than slowly from disk. Cache Memory Principles Cache memory is substantially faster than main memory. A caching system works as follows.. When a processor attempts to read a word of memory, a check is made to see if this in in cache memory… If it is, the data is supplied, If it is not in the cache, a block of main memory, consisting of a fixed number of words is loaded to the cache. Because of the phenomenon of locality of references, when a block of data is fetched into the cache, it is likely that there will be future references to that same memory location or to other words in the block. Elements of Cache Design While there are a large number of cache implementations, there are a few basic design elements that serve to classify and differentiate cache architectures… Cache Addresses Cache Size Mapping Function Replacement Algorithm Write Policy Line Size Number of Caches Cache Addresses Almost all non-embedded processors support virtual memory. Virtual memory in essence allows a program to address memory from a logical point of view without needing to worry about the amount of physical memory available. When virtual addresses are used the designer may choose to place the cache between the MMU (memory management unit) and the processor or between the MMU and main memory. The disadvantage of virtual memory is that most virtual memory systems supply each application with the same virtual memory address space (each application sees virtual memory starting at memory address 0), which means the cache memory must be completely flushed with each application context switch or extra bits must be added to each line of the cache to identify which virtual address space the address refers to. Cache Size We would like the size of the cache to be small enough so that the overall average cost per bit is close to that of main memory alone and large enough so that the overall average access time is close to that of the cache alone. Also, larger caches are slightly slower than smaller ones. Mapping Function Because there are fewer cache lines than main memory blocks, an algorithm is needed for mapping main memory blocks into cache lines. The choice of mapping function dictates how the cache is organized. Three techniques can be used… Direct – simplest technique, maps each block of main memory into only one possible cache line Associative – Each main memory block to be loaded into any line of the cache Set Associative – exhibits the strengths of both the direct and associative approaches while reducing their disadvantages For detailed explanations of each approach – read the text book (page 148 – 154) Replacement Algorithm For associative and set associating mapping a replacement algorithm is needed to determine which of the existing blocks in the cache must be replaced by a new block. There are four common approaches… LRU (Least recently used) FIFO (First in first out) LFU (Least frequently used) Random selection Write Policy When a block resident in the cache is to be replaced, there are two cases to consider If no writes to that block have happened in the cache – discard it If a write has occurred, a process needs to be initiated where the changes in the cache are propagated back to the main memory. There are several approaches to achieve this including… Write Through – all writes to the cache are done to the main memory as well at the point of the change Write Back – when a block is replaced, all dirty bits are written back to main memory The problem is complicated when we have multiple caches, there are techniques to accommodate for this but I have not summarized them. Line Size When a block of data is retrieved and placed in the cache, not only the desired word but also some number of adjacent words are retrieved. As the block size increases from very small to larger sizes, the hit ratio will at first increase because of the principle of locality, which states that the data in the vicinity of a referenced word are likely to be referenced in the near future. As the block size increases, more useful data are brought into cache. The hit ratio will begin to decrease as the block becomes even bigger and the probability of using the newly fetched information becomes less than the probability of using the newly fetched information that has to be replaced. Two specific effects come into play… Larger blocks reduce the number of blocks that fit into a cache. Because each block fetch overwrites older cache contents, a small number of blocks results in data being overwritten shortly after they are fetched. As a block becomes larger, each additional word is farther from the requested word and therefore less likely to be needed in the near future. The relationship between block size and hit ratio is complex, and no set approach is judged to be the best in all circumstances.   Pentium 4 and ARM cache organizations The processor core consists of four major components: Fetch/decode unit – fetches program instruction in order from the L2 cache, decodes these into a series of micro-operations, and stores the results in the L2 instruction cache Out-of-order execution logic – Schedules execution of the micro-operations subject to data dependencies and resource availability – thus micro-operations may be scheduled for execution in a different order than they were fetched from the instruction stream. As time permits, this unit schedules speculative execution of micro-operations that may be required in the future Execution units – These units execute micro-operations, fetching the required data from the L1 data cache and temporarily storing results in registers Memory subsystem – This unit includes the L2 and L3 caches and the system bus, which is used to access main memory when the L1 and L2 caches have a cache miss and to access the system I/O resources

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  • What is the canonical resource on multi-tenancy web applications using ruby + rails

    - by AlexC
    What is the canonical resource on multi-tenancy web applications using ruby + rails. There are a number of ways to develop rails apps using cloud capabilities with real elastic properties but there seems to be a lack of clarity with how to achieve multitenancy, specifically at the model / data level. Is there a canonical resource on options to developing multitenancy rails applications with the required characteristics of data seperation, security, concurrency and contention required by an enterprise level cloud application.

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  • Choosing the right Design Pattern

    - by Carl Sagan
    I've always recognized the importance of utilizing design patterns. I'm curious as to how other developers go about choosing the most appropriate one. Do you use a series of characteristics (like a flowchart) to help you decide? For example: If objects are related, but we do not want to specify concrete class, consider Abstract When instantiation is left to derived classes, consider Factory Need to access elements of an aggregate object sequentially, try Iterator or something similar?

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  • What's new in ASP.NET MVC 2.0?

    Microsoft Visual Studio 2010 and .NET framework 4.0 bring many new exciting features for developers. One of them is the improved ASP.NET MVC 2.0. This article focuses on the new and improved characteristics in this popular web application framework from Microsoft.

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  • What's new in ASP.NET MVC 2.0?

    Microsoft Visual Studio 2010 and .NET framework 4.0 bring many new exciting features for developers. One of them is the improved ASP.NET MVC 2.0. This article focuses on the new and improved characteristics in this popular web application framework from Microsoft.

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  • iOS bluetooth low energy not detecting peripherals

    - by user3712524
    My app won't detect peripherals. Im using light blue to simulate a bluetooth low energy peripheral and my app just won't sense it. I even installed light blue on two devices to make sure it was generating a peripheral signal properly and it is. Any suggestions? My labels are updating and the NSLog is showing that the scanning is starting. Thanks in advance. #import <UIKit/UIKit.h> #import <CoreBluetooth/CoreBluetooth.h> @interface ViewController : UIViewController @property (weak, nonatomic) IBOutlet UITextField *navDestination; @end #import "ViewController.h" @implementation ViewController - (IBAction)connect:(id)sender { } - (IBAction)navDestination:(id)sender { NSString *destinationText = self.navDestination.text; } - (void)viewDidLoad { } - (void)viewWillDisappear:(BOOL)animated { [super viewWillDisappear:animated]; } - (void)didReceiveMemoryWarning { [super didReceiveMemoryWarning]; // Dispose of any resources that can be recreated. } @end #import <UIKit/UIKit.h> #import "ViewController.h" @interface BlueToothViewController : UIViewController @property (strong, nonatomic) CBCentralManager *centralManager; @property (strong, nonatomic) CBPeripheral *discoveredPerepheral; @property (strong, nonatomic) NSMutableData *data; @property (strong, nonatomic) IBOutlet UITextView *textview; @property (weak, nonatomic) IBOutlet UILabel *charLabel; @property (weak, nonatomic) IBOutlet UILabel *isConnected; @property (weak, nonatomic) IBOutlet UILabel *myPeripherals; @property (weak, nonatomic) IBOutlet UILabel *aLabel; - (void)centralManagerDidUpdateState:(CBCentralManager *)central; - (void)centralManger:(CBCentralManager *)central didDiscoverPeripheral: (CBPeripheral *)peripheral advertisementData:(NSDictionary *)advertisementData RSSI:(NSNumber *)RSSI; -(void)centralManager:(CBCentralManager *)central didFailToConnectPeripheral:(CBPeripheral *)peripheral error:(NSError *)error; -(void)cleanup; -(void)centralManager:(CBCentralManager *)central didConnectPeripheral:(CBPeripheral *)peripheral; -(void)peripheral:(CBPeripheral *)peripheral didDiscoverServices:(NSError *)error; -(void)peripheral:(CBPeripheral *)peripheral didDiscoverCharacteristicsForService:(CBService *)service error:(NSError *)error; -(void)centralManager:(CBCentralManager *)central didDisconnectPeripheral:(CBPeripheral *)peripheral error:(NSError *)error; -(void)peripheral:(CBPeripheral *)peripheral didUpdateValueForCharacteristic:(CBCharacteristic *)characteristic error:(NSError *)error; -(void)peripheral:(CBPeripheral *)peripheral didUpdateNotificationStateForCharacteristic:(CBCharacteristic *)characteristic error:(NSError *)error; @end @interface BlueToothViewController () @end @implementation BlueToothViewController - (id)initWithNibName:(NSString *)nibNameOrNil bundle:(NSBundle *)nibBundleOrNil { self = [super initWithNibName:nibNameOrNil bundle:nibBundleOrNil]; if (self) { // Custom initialization } return self; } - (void)viewDidLoad { _centralManager = [[CBCentralManager alloc]initWithDelegate:self queue:nil options:nil]; _data = [[NSMutableData alloc]init]; } - (void)viewWillDisappear:(BOOL)animated { [super viewWillDisappear:animated]; [_centralManager stopScan]; } - (void)didReceiveMemoryWarning { [super didReceiveMemoryWarning]; // Dispose of any resources that can be recreated. } - (void)centralManagerDidUpdateState:(CBCentralManager *)central { //you should test all scenarios if (central.state == CBCentralManagerStateUnknown) { self.aLabel.text = @"I dont do anything because my state is unknown."; return; } if (central.state == CBCentralManagerStatePoweredOn) { //scan for devices [_centralManager scanForPeripheralsWithServices:nil options:@{ CBCentralManagerScanOptionAllowDuplicatesKey : @YES }]; NSLog(@"Scanning Started"); } if (central.state == CBCentralManagerStateResetting) { self.aLabel.text = @"I dont do anything because my state is resetting."; return; } if (central.state == CBCentralManagerStateUnsupported) { self.aLabel.text = @"I dont do anything because my state is unsupported."; return; } if (central.state == CBCentralManagerStateUnauthorized) { self.aLabel.text = @"I dont do anything because my state is unauthorized."; return; } if (central.state == CBCentralManagerStatePoweredOff) { self.aLabel.text = @"I dont do anything because my state is powered off."; return; } } - (void)centralManger:(CBCentralManager *)central didDiscoverPeripheral:(CBPeripheral *)peripheral advertisementData:(NSDictionary *)advertisementData RSSI:(NSNumber *)RSSI { NSLog(@"Discovered %@ at %@", peripheral.name, RSSI); self.myPeripherals.text = [NSString stringWithFormat:@"%@%@",peripheral.name, RSSI]; if (_discoveredPerepheral != peripheral) { //save a copy of the peripheral _discoveredPerepheral = peripheral; //and connect NSLog(@"Connecting to peripheral %@", peripheral); [_centralManager connectPeripheral:peripheral options:nil]; self.aLabel.text = [NSString stringWithFormat:@"%@", peripheral]; } } -(void)centralManager:(CBCentralManager *)central didFailToConnectPeripheral:(CBPeripheral *)peripheral error:(NSError *)error { NSLog(@"Failed to connect"); [self cleanup]; } -(void)cleanup { //see if we are subscribed to a characteristic on the peripheral if (_discoveredPerepheral.services != nil) { for (CBService *service in _discoveredPerepheral.services) { if (service.characteristics != nil) { for (CBCharacteristic *characteristic in service.characteristics) { if ([characteristic.UUID isEqual:[CBUUID UUIDWithString:@"508EFF8E-F541-57EF-BD82-B0B4EC504CA9"]]) { if (characteristic.isNotifying) { [_discoveredPerepheral setNotifyValue:NO forCharacteristic:characteristic]; return; } } } } } } [_centralManager cancelPeripheralConnection:_discoveredPerepheral]; } -(void)centralManager:(CBCentralManager *)central didConnectPeripheral:(CBPeripheral *)peripheral { NSLog(@"Connected"); [_centralManager stopScan]; NSLog(@"Scanning stopped"); self.isConnected.text = [NSString stringWithFormat:@"Connected"]; [_data setLength:0]; peripheral.delegate = self; [peripheral discoverServices:nil]; } -(void)peripheral:(CBPeripheral *)peripheral didDiscoverServices:(NSError *)error { if (error) { [self cleanup]; return; } for (CBService *service in peripheral.services) { [peripheral discoverCharacteristics:nil forService:service]; } //discover other characteristics } -(void)peripheral:(CBPeripheral *)peripheral didDiscoverCharacteristicsForService:(CBService *)service error:(NSError *)error { if (error) { [self cleanup]; return; } for (CBCharacteristic *characteristic in service.characteristics) { [peripheral setNotifyValue:YES forCharacteristic:characteristic]; } } -(void)peripheral:(CBPeripheral *)peripheral didUpdateValueForCharacteristic:(CBCharacteristic *)characteristic error:(NSError *)error { if (error) { NSLog(@"Error"); return; } NSString *stringFromData = [[NSString alloc]initWithData:characteristic.value encoding:NSUTF8StringEncoding]; self.charLabel.text = [NSString stringWithFormat:@"%@", stringFromData]; //Have we got everything we need? if ([stringFromData isEqualToString:@"EOM"]) { [_textview setText:[[NSString alloc]initWithData:self.data encoding:NSUTF8StringEncoding]]; [peripheral setNotifyValue:NO forCharacteristic:characteristic]; [_centralManager cancelPeripheralConnection:peripheral]; } } -(void)peripheral:(CBPeripheral *)peripheral didUpdateNotificationStateForCharacteristic:(CBCharacteristic *)characteristic error:(NSError *)error { if ([characteristic.UUID isEqual:nil]) { return; } if (characteristic.isNotifying) { NSLog(@"Notification began on %@", characteristic); } else { [_centralManager cancelPeripheralConnection:peripheral]; } } -(void)centralManager:(CBCentralManager *)central didDisconnectPeripheral:(CBPeripheral *)peripheral error:(NSError *)error { _discoveredPerepheral = nil; self.isConnected.text = [NSString stringWithFormat:@"Connecting..."]; [_centralManager scanForPeripheralsWithServices:nil options:@{ CBCentralManagerScanOptionAllowDuplicatesKey : @YES}]; } @end

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  • Mobile App Data Syncronization

    - by Matt Rogish
    Let's say I have a mobile app that uses HTML5 SQLite DB (and/or the HTML5 key-value store). Assets (media files, PDFs, etc.) are stored locally on the mobile device. Luckily enough, the mobile device is a read-only copy of the "centralized" storage, so the mobile device won't have to propagate changes upstream. However, as the server changes assets (creates new ones, modifies existing, deletes old ones) I need to propagate those changes back to the mobile app. Assume that server changes are grouped into changesets (version number n) that contain some information (added element XYZ, deleted id = 45, etc.) and that the mobile device has limited CPU/bandwidth, so most of the processing has to take place on the server. I can think of a couple of methods to do this. All have trade-offs and at this point, I'm unsure which is the right course of action... Method 1: For change set n, store the "diff" of the current n and previous n-1. When a client with version y asks if there have been any changes, send the change sets from version y up to the current version. e.g. added item 334, contents: xxx. Deleted picture 44. Deleted PDF 11. Changed 33. added picture 99. Characteristics: Diffs take up space, although in theory would be kept small. However, all diffs must be kept around indefinitely (should a v1 app have not been updated for a year, must apply v2..v100). High latency devices (mobile apps) will incur a penalty to send lots of small files (assume cannot be zipped or tarr'd up into one file) Very few server CPU resources required, as all it does is send the client a list of files "Dumb" - if I change an item in change set 3, and change it to something else in 4, the client is going to perform both actions, even though #3 is rendered moot by #4. Or, if an asset is added in #4 and removed in #5 - the client will download a file just to delete it later. Method 2: Very similar to method 1 except on the server, do some sort of a diff between the change sets represented by the app version and server version. Package that up and send that single change set to the client. Characteristics: Client-efficient: The client only has to process one file, duplicate or irrelevant changes are stripped out. Server CPU/space intensive. The change sets must be diff'd and then written out to a file that is then sent to the client. Makes diff server scalability an issue. Possibly ways to cache the results and re-use them, but in the wild there's likely to be a lot of different versions so the diff re-use has a limit Diff algorithm is complicated. The change sets must be structured in such a way that an efficient and effective diff can be performed. Method 3: Instead of keeping diffs, write out the entire versioned asset collection to a mobile-database import file. When client requests an update, send the entire database to client and have them update their assets appropriately. Characteristics: Conceptually simple -- easy to develop and deploy Very inefficient as the client database is restored every update. If only one new thing was added, the whole database is refreshed. Server space and CPU efficient. Only the latest version DB needs kept around and the server just throws the file to the client. Others?? Thoughts? Thanks!!

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