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  • XNA: What is the point of Unload()?

    - by Rosarch
    XNA games have an Unload() method, where content is supposed to be unloaded. But what is the point of this? If all the content is being unloaded, then the game must be exiting, in which case everything would be garbage collected anyway, right?

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  • Objective-c when to release objects

    - by Chris
    -(IBAction)registerUpdate:(id)sender { HTTPRequest* request = [[HTTPRequest alloc] initWithUrl:@"http://www.yahoo.com" delegate:self]; [request doRequest]; } The HTTPRequest makes an asynchronous request and calls the onHTTPResponse method in the current class. My question is do I have to release request? My guess is that I'm supposed to make it an instance variable? [NSString stringWithFormat:@"Data received: %@", [[NSString alloc] initWithData:data encoding:NSASCIIStringEncoding]]; How would I release that string object, or should I assign it to a variable?

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  • Can I just release the top object (iPhone)?

    - by yar
    If I release the object that's holding a reference to the variable that I need to release, is that sufficient? Or must I release at every level of the containment hierarchy? I fear that my logic comes from working with a garbage collector for too long. For instance, I assigned to this property of a UIPickerView instance by hand instead of using IB @property(nonatomic, assign) id<UIPickerViewDelegate> delegate Since it's an assign property, I can't just release the reference after I assign it. When I finally release my UIPickerView instance, do I need to do this: [singlePicker.delegate release]; [singlePicker release]; or is the second line sufficient? Also: Are these assign properties the norm, or is that mostly for Interface Builder? I thought that retain properties were the normal thing to expect.

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  • How to copy a structure with pointers to data inside (so to copy pointers and data they point to)?

    - by Kabumbus
    so I have a structure like struct GetResultStructure { int length; char* ptr; }; I need a way to make a full copy of it meaning I need a copy to have a structure with new ptr poinnting on to copy of data I had in original structure. Is It any how possible? I mean any structure I have which contains ptrs will have some fields with its lengths I need a function that would copy my structure coping all ptrs and data they point to by given array of lengthes... Any cool boost function for it? Or any way how to create such function?

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  • The difference between delete and delete [] in C++

    - by Ilya Melamed
    I've written a class that contains two pointers, one is char* color_ and one in vertexesset* vertex_ where vertexesset is a class I created. In the destractor I've written at start delete [] color_; delete [] vertex_; When It came to the destructor it gave me a segmentation fault. Then I changed the destructor to: delete [] color_; delete vertex_; And now it works fine. What is the difference between the two?

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  • Does LINQ require significantly more processing cycles and memory than lower-level data iteration techniques?

    - by Matthew Patrick Cashatt
    Background I am recently in the process of enduring grueling tech interviews for positions that use the .NET stack, some of which include silly questions like this one, and some questions that are more valid. I recently came across an issue that may be valid but I want to check with the community here to be sure. When asked by an interviewer how I would count the frequency of words in a text document and rank the results, I answered that I would Use a stream object put the text file in memory as a string. Split the string into an array on spaces while ignoring punctuation. Use LINQ against the array to .GroupBy() and .Count(), then OrderBy() said count. I got this answer wrong for two reasons: Streaming an entire text file into memory could be disasterous. What if it was an entire encyclopedia? Instead I should stream one block at a time and begin building a hash table. LINQ is too expensive and requires too many processing cycles. I should have built a hash table instead and, for each iteration, only added a word to the hash table if it didn't otherwise exist and then increment it's count. The first reason seems, well, reasonable. But the second gives me more pause. I thought that one of the selling points of LINQ is that it simply abstracts away lower-level operations like hash tables but that, under the veil, it is still the same implementation. Question Aside from a few additional processing cycles to call any abstracted methods, does LINQ require significantly more processing cycles to accomplish a given data iteration task than a lower-level task (such as building a hash table) would?

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  • Creating foreign words' learning site with memory technique (Web 2.0)? Will it work?

    - by Michal P.
    I would like to earn a little money for realizing a good, simple project. My idea is to build a website for learning of chosen by me language (for users knowing English) using mnemonics. Users would be encourage to enter English words with translation to another language and describing the way, how to remember a foreign language word (an association link). Example: if I choose learning Spanish for people who knows English well, it would look like that: every user would be encourage to enter a way to remember a chosen by him/her Spanish word. So he/she would enter to the dictionary (my site database) ,e.g., English word: beach - playa (Spanish word). Then he/she would describe the method to remember Spanish word, e.g., "Image that U r on the beach and U play volleyball" - we have the word play and recall playa (mnemonics). I would like to give possibility of pic hotlinks, encourage for fun or little shocking memory links which is -- in the art of memory -- good. I would choose a language to take a niche of Google Search. The big question is if I don't lose my time on it?? (Maybe I need to find prototype way to check that idea?)

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  • From the Tips Box: Xbox Output on Two Screens, High Tech Halloween Props, and Old Flash Drives as Password Reset Disks

    - by Jason Fitzpatrick
    Once a week we round up some great reader tips and share them with everyone, this week we’re looking at outputting your Xbox 360 to two screens, spooky high-tech Halloween props, and recycling old flash drives as password reset disks. HTG Explains: What is the Windows Page File and Should You Disable It? How To Get a Better Wireless Signal and Reduce Wireless Network Interference How To Troubleshoot Internet Connection Problems

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  • Avoiding background and main menu reloads (white flash) when users navigate my site?

    - by gus
    Not a major problem, but I would like to understand more about how some websites can serve different pages to a navigating user, such that the browser doesn't visibly pass through a blank white page. Whereas some sites cause the browser to display the white page for up to a few seconds. I can imagine this is partly due to network latency, but are there any other factors? Can I cause the background image / color not to flash white?

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  • Chrome 5, une beta riche en nouvelles fonctionnalités et encore plus rapide : Flash, HTML 5 et navig

    Mise à jour du 05/05/10 NB : Les commentaires sur cette mise à jour commencent ici dans le topic Chrome 5, une nouvelle beta qui vaut le détour Encore plus rapide, elle intègre de très nombreuses fonctionnalités : Flash, HTML 5 et navigation privée au menu Chrome 5.0.375.29 vient d'arriver sur le beta channel. Cette fois-ci, et contrairement à la précédente (lire ci-avant), on peut qualifier cette évolution d'importante tant les nouvelles fonctionnalités et les améliorations sont nom...

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  • Should I be running VM's(Virtual Box) for development on the same hdd as my os or a external usb (2.0) HDD or usb (2.0) flash drive

    - by J. Brown
    I have a mac book pro (7200 rpm / 8GB ram) and I like the idea of virtualized development environments as I like to experiment with different technologies and don't like to have environmental cross contamination. I would like to know for the vm's I run (rarely 2 at time..almost always 1 vm at a time) should the virtual hdd be on my laptops native hdd or some external form (usb hdd, usb flash, or since i have mac express card based sad ?). I don't mind maxing out my ram to 16GB if thats a better option to have in the mix. Thank you

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  • How to write image of a floppy disk to a flash drive?

    - by Usman Ajmal
    I have created an image of a floppy disk by executing: dd if=/dev/fd0 of=/home/myFloppy.img My floppy disk is no more working now. So I am thinking now if it's possible to write the image of that floppy to a flash drive and then i may boot my machine from the flash drive. My machine's BIOS has the option of 'Boot from USB'.

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  • what version flash player has to be downloaded to play .swf files on Windows mobile 6.5?

    - by manraj82
    Hi guys, I'm trying to view websites with flash content in IE on a window mobile 6.5 device[HTC touch HD2].It says it has not got the right flash player.i tried to install the player but the device giving me an error,its saying the installer is not a valid pocket pc application. Has anyone else had a similar problem? If you have and sorted it could please advice me how to sort it? thanks

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  • SAP dévoile Business Object 4.0, la nouvelle version de sa solution BI intègre la mobilité, les réseaux sociaux et le « in-memory »

    SAP dévoile Business Object 4.0 La nouvelle version de sa solution BI intègre la mobilité, les réseaux sociaux et le « in-memory » SAP vient de dévoiler Business Object 4.0, la prochaine version de sa plate-forme de nouvelle génération de Business Intelligence et de Gestion d'Information d'Entreprise (EIM). [IMG]http://ftp-developpez.com/gordon-fowler/SAP/Slide-5-SAP-BusinessObjects-4.0-Event-Insight2.jpg[/IMG] Après SAP ByDesign 2.6, sa suite ERP en mode SaaS (qui arrive avec un tout nouveau SDK), Business Object 4.0 est la deuxième très grosse annonce de cette année 2011 que Nicolas Sekkaki, Direc...

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  • Boost Netbook Speed with an SD Card & ReadyBoost

    - by Matthew Guay
    Looking for a way to increase the performance of your netbook?  Here’s how you can use a standard SD memory card or a USB flash drive to boost performance with ReadyBoost. Most netbooks ship with 1Gb of Ram, and many older netbooks shipped with even less.  Even if you want to add more ram, often they can only be upgraded to a max of 2GB.  With ReadyBoost in Windows 7, it’s easy to boost your system’s performance with flash memory.  If your netbook has an SD card slot, you can insert a memory card into it and just leave it there to always boost your netbook’s memory; otherwise, you can use a standard USB flash drive the same way. Also, you can use ReadyBoost on any desktop or laptop; ones with limited memory will see the most performance increase from using it. Please Note:  ReadyBoost requires at least 256Mb of free space on your flash drive, and also requires minimum read/write speeds.  Most modern memory cards or flash drives meet these requirements, but be aware that an old card may not work with it. Using ReadyBoost Insert an SD card into your card reader, or connect a USB flash drive to a USB port on your computer.  Windows will automatically see if your flash memory is ReadyBoost capable, and if so, you can directly choose to speed up your computer with ReadyBoost. The ReadyBoost settings dialog will open when you select this.  Choose “Use this device” and choose how much space you want ReadyBoost to use. Click Ok, and Windows will setup ReadyBoost and start using it to speed up your computer.  It will automatically use ReadyBoost whenever the card is connected to the computer. When you view your SD card or flash drive in Explorer, you will notice a ReadyBoost file the size you chose before.  This will be deleted when you eject your card or flash drive. If you need to remove your drive to use elsewhere, simply eject as normal. Windows will inform you that the drive is currently being used.  Make sure you have closed any programs or files you had open from the drive, and then press Continue to stop ReadyBoost and eject your drive. If you remove the drive without ejecting it, the ReadyBoost file may still remain on the drive.  You can delete this to save space on the drive, and the cache will be recreated when you use ReadyBoost next time. Conclusion Although ReadyBoost may not make your netbook feel like a Core i7 laptop with 6GB of RAM, it will still help performance and make multitasking even easier.  Also, if you have, say, a memory stick and a flash drive, you can use both of them with ReadyBoost for the maximum benefit.  We have even noticed better battery life when multitasking with ReadyBoost, as it lets you use your hard drive less.  SD cards and thumb drives are relatively cheap today, and many of us have several already, so this is a great way to improve netbook performance cheaply. Similar Articles Productive Geek Tips Speed up Your Windows Vista Computer with ReadyBoostSet the Speed Dial as the Opera Startup PageAsk the Readers: What are Your Computer’s Hardware Specs?Understanding Windows Vista Aero Glass RequirementsReplace Google Chrome’s New Tab Page with Speed Dial TouchFreeze Alternative in AutoHotkey The Icy Undertow Desktop Windows Home Server – Backup to LAN The Clear & Clean Desktop Use This Bookmarklet to Easily Get Albums Use AutoHotkey to Assign a Hotkey to a Specific Window Latest Software Reviews Tinyhacker Random Tips DVDFab 6 Revo Uninstaller Pro Registry Mechanic 9 for Windows PC Tools Internet Security Suite 2010 Recycle ! Find That Elusive Icon with FindIcons Looking for Good Windows Media Player 12 Plug-ins? Find Out the Celebrity You Resemble With FaceDouble Whoa ! Use Printflush to Solve Printing Problems

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  • C# Performance Pitfall – Interop Scenarios Change the Rules

    - by Reed
    C# and .NET, overall, really do have fantastic performance in my opinion.  That being said, the performance characteristics dramatically differ from native programming, and take some relearning if you’re used to doing performance optimization in most other languages, especially C, C++, and similar.  However, there are times when revisiting tricks learned in native code play a critical role in performance optimization in C#. I recently ran across a nasty scenario that illustrated to me how dangerous following any fixed rules for optimization can be… The rules in C# when optimizing code are very different than C or C++.  Often, they’re exactly backwards.  For example, in C and C++, lifting a variable out of loops in order to avoid memory allocations often can have huge advantages.  If some function within a call graph is allocating memory dynamically, and that gets called in a loop, it can dramatically slow down a routine. This can be a tricky bottleneck to track down, even with a profiler.  Looking at the memory allocation graph is usually the key for spotting this routine, as it’s often “hidden” deep in call graph.  For example, while optimizing some of my scientific routines, I ran into a situation where I had a loop similar to: for (i=0; i<numberToProcess; ++i) { // Do some work ProcessElement(element[i]); } .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } This loop was at a fairly high level in the call graph, and often could take many hours to complete, depending on the input data.  As such, any performance optimization we could achieve would be greatly appreciated by our users. After a fair bit of profiling, I noticed that a couple of function calls down the call graph (inside of ProcessElement), there was some code that effectively was doing: // Allocate some data required DataStructure* data = new DataStructure(num); // Call into a subroutine that passed around and manipulated this data highly CallSubroutine(data); // Read and use some values from here double values = data->Foo; // Cleanup delete data; // ... return bar; Normally, if “DataStructure” was a simple data type, I could just allocate it on the stack.  However, it’s constructor, internally, allocated it’s own memory using new, so this wouldn’t eliminate the problem.  In this case, however, I could change the call signatures to allow the pointer to the data structure to be passed into ProcessElement and through the call graph, allowing the inner routine to reuse the same “data” memory instead of allocating.  At the highest level, my code effectively changed to something like: DataStructure* data = new DataStructure(numberToProcess); for (i=0; i<numberToProcess; ++i) { // Do some work ProcessElement(element[i], data); } delete data; Granted, this dramatically reduced the maintainability of the code, so it wasn’t something I wanted to do unless there was a significant benefit.  In this case, after profiling the new version, I found that it increased the overall performance dramatically – my main test case went from 35 minutes runtime down to 21 minutes.  This was such a significant improvement, I felt it was worth the reduction in maintainability. In C and C++, it’s generally a good idea (for performance) to: Reduce the number of memory allocations as much as possible, Use fewer, larger memory allocations instead of many smaller ones, and Allocate as high up the call stack as possible, and reuse memory I’ve seen many people try to make similar optimizations in C# code.  For good or bad, this is typically not a good idea.  The garbage collector in .NET completely changes the rules here. In C#, reallocating memory in a loop is not always a bad idea.  In this scenario, for example, I may have been much better off leaving the original code alone.  The reason for this is the garbage collector.  The GC in .NET is incredibly effective, and leaving the allocation deep inside the call stack has some huge advantages.  First and foremost, it tends to make the code more maintainable – passing around object references tends to couple the methods together more than necessary, and overall increase the complexity of the code.  This is something that should be avoided unless there is a significant reason.  Second, (unlike C and C++) memory allocation of a single object in C# is normally cheap and fast.  Finally, and most critically, there is a large advantage to having short lived objects.  If you lift a variable out of the loop and reuse the memory, its much more likely that object will get promoted to Gen1 (or worse, Gen2).  This can cause expensive compaction operations to be required, and also lead to (at least temporary) memory fragmentation as well as more costly collections later. As such, I’ve found that it’s often (though not always) faster to leave memory allocations where you’d naturally place them – deep inside of the call graph, inside of the loops.  This causes the objects to stay very short lived, which in turn increases the efficiency of the garbage collector, and can dramatically improve the overall performance of the routine as a whole. In C#, I tend to: Keep variable declarations in the tightest scope possible Declare and allocate objects at usage While this tends to cause some of the same goals (reducing unnecessary allocations, etc), the goal here is a bit different – it’s about keeping the objects rooted for as little time as possible in order to (attempt) to keep them completely in Gen0, or worst case, Gen1.  It also has the huge advantage of keeping the code very maintainable – objects are used and “released” as soon as possible, which keeps the code very clean.  It does, however, often have the side effect of causing more allocations to occur, but keeping the objects rooted for a much shorter time. Now – nowhere here am I suggesting that these rules are hard, fast rules that are always true.  That being said, my time spent optimizing over the years encourages me to naturally write code that follows the above guidelines, then profile and adjust as necessary.  In my current project, however, I ran across one of those nasty little pitfalls that’s something to keep in mind – interop changes the rules. In this case, I was dealing with an API that, internally, used some COM objects.  In this case, these COM objects were leading to native allocations (most likely C++) occurring in a loop deep in my call graph.  Even though I was writing nice, clean managed code, the normal managed code rules for performance no longer apply.  After profiling to find the bottleneck in my code, I realized that my inner loop, a innocuous looking block of C# code, was effectively causing a set of native memory allocations in every iteration.  This required going back to a “native programming” mindset for optimization.  Lifting these variables and reusing them took a 1:10 routine down to 0:20 – again, a very worthwhile improvement. Overall, the lessons here are: Always profile if you suspect a performance problem – don’t assume any rule is correct, or any code is efficient just because it looks like it should be Remember to check memory allocations when profiling, not just CPU cycles Interop scenarios often cause managed code to act very differently than “normal” managed code. Native code can be hidden very cleverly inside of managed wrappers

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  • tile_static, tile_barrier, and tiled matrix multiplication with C++ AMP

    - by Daniel Moth
    We ended the previous post with a mechanical transformation of the C++ AMP matrix multiplication example to the tiled model and in the process introduced tiled_index and tiled_grid. This is part 2. tile_static memory You all know that in regular CPU code, static variables have the same value regardless of which thread accesses the static variable. This is in contrast with non-static local variables, where each thread has its own copy. Back to C++ AMP, the same rules apply and each thread has its own value for local variables in your lambda, whereas all threads see the same global memory, which is the data they have access to via the array and array_view. In addition, on an accelerator like the GPU, there is a programmable cache, a third kind of memory type if you'd like to think of it that way (some call it shared memory, others call it scratchpad memory). Variables stored in that memory share the same value for every thread in the same tile. So, when you use the tiled model, you can have variables where each thread in the same tile sees the same value for that variable, that threads from other tiles do not. The new storage class for local variables introduced for this purpose is called tile_static. You can only use tile_static in restrict(direct3d) functions, and only when explicitly using the tiled model. What this looks like in code should be no surprise, but here is a snippet to confirm your mental image, using a good old regular C array // each tile of threads has its own copy of locA, // shared among the threads of the tile tile_static float locA[16][16]; Note that tile_static variables are scoped and have the lifetime of the tile, and they cannot have constructors or destructors. tile_barrier In amp.h one of the types introduced is tile_barrier. You cannot construct this object yourself (although if you had one, you could use a copy constructor to create another one). So how do you get one of these? You get it, from a tiled_index object. Beyond the 4 properties returning index objects, tiled_index has another property, barrier, that returns a tile_barrier object. The tile_barrier class exposes a single member, the method wait. 15: // Given a tiled_index object named t_idx 16: t_idx.barrier.wait(); 17: // more code …in the code above, all threads in the tile will reach line 16 before a single one progresses to line 17. Note that all threads must be able to reach the barrier, i.e. if you had branchy code in such a way which meant that there is a chance that not all threads could reach line 16, then the code above would be illegal. Tiled Matrix Multiplication Example – part 2 So now that we added to our understanding the concepts of tile_static and tile_barrier, let me obfuscate rewrite the matrix multiplication code so that it takes advantage of tiling. Before you start reading this, I suggest you get a cup of your favorite non-alcoholic beverage to enjoy while you try to fully understand the code. 01: void MatrixMultiplyTiled(vector<float>& vC, const vector<float>& vA, const vector<float>& vB, int M, int N, int W) 02: { 03: static const int TS = 16; 04: array_view<const float,2> a(M, W, vA); 05: array_view<const float,2> b(W, N, vB); 06: array_view<writeonly<float>,2> c(M,N,vC); 07: parallel_for_each(c.grid.tile< TS, TS >(), 08: [=] (tiled_index< TS, TS> t_idx) restrict(direct3d) 09: { 10: int row = t_idx.local[0]; int col = t_idx.local[1]; 11: float sum = 0.0f; 12: for (int i = 0; i < W; i += TS) { 13: tile_static float locA[TS][TS], locB[TS][TS]; 14: locA[row][col] = a(t_idx.global[0], col + i); 15: locB[row][col] = b(row + i, t_idx.global[1]); 16: t_idx.barrier.wait(); 17: for (int k = 0; k < TS; k++) 18: sum += locA[row][k] * locB[k][col]; 19: t_idx.barrier.wait(); 20: } 21: c[t_idx.global] = sum; 22: }); 23: } Notice that all the code up to line 9 is the same as per the changes we made in part 1 of tiling introduction. If you squint, the body of the lambda itself preserves the original algorithm on lines 10, 11, and 17, 18, and 21. The difference being that those lines use new indexing and the tile_static arrays; the tile_static arrays are declared and initialized on the brand new lines 13-15. On those lines we copy from the global memory represented by the array_view objects (a and b), to the tile_static vanilla arrays (locA and locB) – we are copying enough to fit a tile. Because in the code that follows on line 18 we expect the data for this tile to be in the tile_static storage, we need to synchronize the threads within each tile with a barrier, which we do on line 16 (to avoid accessing uninitialized memory on line 18). We also need to synchronize the threads within a tile on line 19, again to avoid the race between lines 14, 15 (retrieving the next set of data for each tile and overwriting the previous set) and line 18 (not being done processing the previous set of data). Luckily, as part of the awesome C++ AMP debugger in Visual Studio there is an option that helps you find such races, but that is a story for another blog post another time. May I suggest reading the next section, and then coming back to re-read and walk through this code with pen and paper to really grok what is going on, if you haven't already? Cool. Why would I introduce this tiling complexity into my code? Funny you should ask that, I was just about to tell you. There is only one reason we tiled our extent, had to deal with finding a good tile size, ensure the number of threads we schedule are correctly divisible with the tile size, had to use a tiled_index instead of a normal index, and had to understand tile_barrier and to figure out where we need to use it, and double the size of our lambda in terms of lines of code: the reason is to be able to use tile_static memory. Why do we want to use tile_static memory? Because accessing tile_static memory is around 10 times faster than accessing the global memory on an accelerator like the GPU, e.g. in the code above, if you can get 150GB/second accessing data from the array_view a, you can get 1500GB/second accessing the tile_static array locA. And since by definition you are dealing with really large data sets, the savings really pay off. We have seen tiled implementations being twice as fast as their non-tiled counterparts. Now, some algorithms will not have performance benefits from tiling (and in fact may deteriorate), e.g. algorithms that require you to go only once to global memory will not benefit from tiling, since with tiling you already have to fetch the data once from global memory! Other algorithms may benefit, but you may decide that you are happy with your code being 150 times faster than the serial-version you had, and you do not need to invest to make it 250 times faster. Also algorithms with more than 3 dimensions, which C++ AMP supports in the non-tiled model, cannot be tiled. Also note that in future releases, we may invest in making the non-tiled model, which already uses tiling under the covers, go the extra step and use tile_static memory on your behalf, but it is obviously way to early to commit to anything like that, and we certainly don't do any of that today. Comments about this post by Daniel Moth welcome at the original blog.

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  • Fatal error: Out of memory (allocated ...) (tried to allocate ... bytes) not due to memory_limit setting

    - by Lorenz Meyer
    Since a few days, I get the following error on my server: Fatal error: Out of memory (allocated 262144) (tried to allocate 393216 bytes) Usually this error is due to a memory consumption that is exceeding the configured memory_limit, but in my case there is no relation. The memory_limit is set to 128MB, and in this case, we not even reach 1MB. Also the server does not have a big load, in fact it is an intranet server, and there are just a few people conected to it. System: Windows Server 2003, 1Go RAM, only 600 MB used. Apache 2.2.4 PHP 5.2.3 This error is appearing randomly. The memory limit reached also is randomly between a few kB to a few MB. Sometimes restarting Apache is required to get rid of the error, sometimes it disapears itself. Restarting Apache or the entire server helps temporarily. Where could this problem come from ? How could I narrow down the error source ?

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