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  • Running C++ AMP kernels on the CPU

    - by Daniel Moth
    One of the FAQs we receive is whether C++ AMP can be used to target the CPU. For targeting multi-core we have a technology we released with VS2010 called PPL, which has had enhancements for VS 11 – that is what you should be using! FYI, it also has a Linux implementation via Intel's TBB which conforms to the same interface. When you choose to use C++ AMP, you choose to take advantage of massively parallel hardware, through accelerators like the GPU. Having said that, you can always use the accelerator class to check if you are running on a system where the is no hardware with a DirectX 11 driver, and decide what alternative code path you wish to follow.  In fact, if you do nothing in code, if the runtime does not find DX11 hardware to run your code on, it will choose the WARP accelerator which will run your code on the CPU, taking advantage of multi-core and SSE2 (depending on the CPU capabilities WARP also uses SSE3 and SSE 4.1 – it does not currently use AVX and on such systems you hopefully have a DX 11 GPU anyway). A few things to know about WARP It is our fallback CPU solution, not intended as a primary target of C++ AMP. WARP stands for Windows Advanced Rasterization Platform and you can read old info on this MSDN page on WARP. What is new in Windows 8 Developer Preview is that WARP now supports DirectCompute, which is what C++ AMP builds on. It is not currently clear if we will have a CPU fallback solution for non-Windows 8 platforms when we ship. When you create a WARP accelerator, its is_emulated property returns true. WARP does not currently support double precision.   BTW, when we refer to WARP, we refer to this accelerator described above. If we use lower case "warp", that refers to a bunch of threads that run concurrently in lock step and share the same instruction. In the VS 11 Developer Preview, the size of warp in our Ref emulator is 4 – Ref is another emulator that runs on the CPU, but it is extremely slow not intended for production, just for debugging. Comments about this post by Daniel Moth welcome at the original blog.

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  • GDD-BR 2010 [1H] VC Panel: Entrepreneurship, Incubation and Venture Capital

    GDD-BR 2010 [1H] VC Panel: Entrepreneurship, Incubation and Venture Capital Speakers: Don Dodge, Eric Acher, Humberto Matsuda, Alex Tabor Track: Panels Time slot: H [17:20 - 18:05] Room: 1 Startups can be built and funded anywhere in the world, not just Silicon Valley. Venture Capital investors are investing in startups globally, and funding incubators to hatch their future investments. Find out how you can get into an incubator, or funded by a Venture Capitalist or Angel Investors. Learn from examples in the USA and hear from local VC investors in this panel discussion. Get your questions answered by real investors. From: GoogleDevelopers Views: 6 0 ratings Time: 37:39 More in Science & Technology

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  • How do .so files avoid problems associated with passing header-only templates like MS dll files have?

    - by Doug T.
    Based on the discussion around this question. I'd like to know how .so files/the ELF format/the gcc toolchain avoid problems passing classes defined purely in header files (like the std library). According to Jan in that answer, the dynamic linker/loader only picks one version of such a class to load if its defined in two .so files. So if two .so files have two definitions, perhaps with different compiler options/etc, the dynamic linker can pick one to use. Is this correct? How does this work with inlining? For example, MSVC inlines templates aggressively. This makes the solution I describe above untenable for dlls. Does Gcc never inline header-only templates like the std library as MSVC does? If so wouldn't that make the functionality of ELF described above ineffective in these cases?

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  • Are there any open source projects for car engine sound simulation?

    - by Petteri Hietavirta
    I have been thinking how to create realistic sound for a car. The main sound is the engine, then all kind of wind, road and suspension sounds. Are there any open source projects for the engine sound simulation? Simply pitching up the sample does not sound too great. The ideal would be to something that allows me to pick type of the engine (i.e. inline-4 vs v-8), add extras like turbo/supercharger whine and finally set the load and rpm. Edit: Something like http://www.sonory.org/examples.html

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  • parallel_for_each from amp.h – part 1

    - by Daniel Moth
    This posts assumes that you've read my other C++ AMP posts on index<N> and extent<N>, as well as about the restrict modifier. It also assumes you are familiar with C++ lambdas (if not, follow my links to C++ documentation). Basic structure and parameters Now we are ready for part 1 of the description of the new overload for the concurrency::parallel_for_each function. The basic new parallel_for_each method signature returns void and accepts two parameters: a grid<N> (think of it as an alias to extent) a restrict(direct3d) lambda, whose signature is such that it returns void and accepts an index of the same rank as the grid So it looks something like this (with generous returns for more palatable formatting) assuming we are dealing with a 2-dimensional space: // some_code_A parallel_for_each( g, // g is of type grid<2> [ ](index<2> idx) restrict(direct3d) { // kernel code } ); // some_code_B The parallel_for_each will execute the body of the lambda (which must have the restrict modifier), on the GPU. We also call the lambda body the "kernel". The kernel will be executed multiple times, once per scheduled GPU thread. The only difference in each execution is the value of the index object (aka as the GPU thread ID in this context) that gets passed to your kernel code. The number of GPU threads (and the values of each index) is determined by the grid object you pass, as described next. You know that grid is simply a wrapper on extent. In this context, one way to think about it is that the extent generates a number of index objects. So for the example above, if your grid was setup by some_code_A as follows: extent<2> e(2,3); grid<2> g(e); ...then given that: e.size()==6, e[0]==2, and e[1]=3 ...the six index<2> objects it generates (and hence the values that your lambda would receive) are:    (0,0) (1,0) (0,1) (1,1) (0,2) (1,2) So what the above means is that the lambda body with the algorithm that you wrote will get executed 6 times and the index<2> object you receive each time will have one of the values just listed above (of course, each one will only appear once, the order is indeterminate, and they are likely to call your code at the same exact time). Obviously, in real GPU programming, you'd typically be scheduling thousands if not millions of threads, not just 6. If you've been following along you should be thinking: "that is all fine and makes sense, but what can I do in the kernel since I passed nothing else meaningful to it, and it is not returning any values out to me?" Passing data in and out It is a good question, and in data parallel algorithms indeed you typically want to pass some data in, perform some operation, and then typically return some results out. The way you pass data into the kernel, is by capturing variables in the lambda (again, if you are not familiar with them, follow the links about C++ lambdas), and the way you use data after the kernel is done executing is simply by using those same variables. In the example above, the lambda was written in a fairly useless way with an empty capture list: [ ](index<2> idx) restrict(direct3d), where the empty square brackets means that no variables were captured. If instead I write it like this [&](index<2> idx) restrict(direct3d), then all variables in the some_code_A region are made available to the lambda by reference, but as soon as I try to use any of those variables in the lambda, I will receive a compiler error. This has to do with one of the direct3d restrictions, where only one type can be capture by reference: objects of the new concurrency::array class that I'll introduce in the next post (suffice for now to think of it as a container of data). If I write the lambda line like this [=](index<2> idx) restrict(direct3d), all variables in the some_code_A region are made available to the lambda by value. This works for some types (e.g. an integer), but not for all, as per the restrictions for direct3d. In particular, no useful data classes work except for one new type we introduce with C++ AMP: objects of the new concurrency::array_view class, that I'll introduce in the post after next. Also note that if you capture some variable by value, you could use it as input to your algorithm, but you wouldn’t be able to observe changes to it after the parallel_for_each call (e.g. in some_code_B region since it was passed by value) – the exception to this rule is the array_view since (as we'll see in a future post) it is a wrapper for data, not a container. Finally, for completeness, you can write your lambda, e.g. like this [av, &ar](index<2> idx) restrict(direct3d) where av is a variable of type array_view and ar is a variable of type array - the point being you can be very specific about what variables you capture and how. So it looks like from a large data perspective you can only capture array and array_view objects in the lambda (that is how you pass data to your kernel) and then use the many threads that call your code (each with a unique index) to perform some operation. You can also capture some limited types by value, as input only. When the last thread completes execution of your lambda, the data in the array_view or array are ready to be used in the some_code_B region. We'll talk more about all this in future posts… (a)synchronous Please note that the parallel_for_each executes as if synchronous to the calling code, but in reality, it is asynchronous. I.e. once the parallel_for_each call is made and the kernel has been passed to the runtime, the some_code_B region continues to execute immediately by the CPU thread, while in parallel the kernel is executed by the GPU threads. However, if you try to access the (array or array_view) data that you captured in the lambda in the some_code_B region, your code will block until the results become available. Hence the correct statement: the parallel_for_each is as-if synchronous in terms of visible side-effects, but asynchronous in reality.   That's all for now, we'll revisit the parallel_for_each description, once we introduce properly array and array_view – coming next. Comments about this post by Daniel Moth welcome at the original blog.

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  • Why do we need a format for binary executable files

    - by user3671483
    When binary files (i.e. executables) are saved they usually have a format (e.g. ELF or .out) where we have a header containing pointers to where data or code is stored inside the file. But why don't we store the binary files directly in the form of sequence of machine instructions.Why do we need to store data separately from the code?Secondly when the assembler creates a binary file is the file is among the above formats?

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  • La evolución en lenguajes de programación, DART en detalles

    La evolución en lenguajes de programación, DART en detalles En este programa presentaremos una visión general de las novedades tecnológicas desde el equipo de relaciones para desarrolladores de la región de sur de Latinoamérica. Seguiremos presentando nuestro enfoque de desarrollo, ingeniería y las mejores prácticas para implementar tecnología Google favoreciendo la evolución de soluciones tecnológicas. Luego nos introduciremos en un escenario técnico en donde analizaremos la evolución en los lenguajes de programación para desarrolladores como DART. Finalmente estaremos conversando con la comunidad de desarrollo, resolviendo un desafío técnico y premiando todo el talento regional. From: GoogleDevelopers Views: 0 0 ratings Time: 02:00:00 More in Education

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  • Should I close database connections after use in PHP?

    - by Sprottenwels
    I wonder if I should close any unnecessary database connection inside of my PHP scripts. I am aware of the fact that database connections are closed implicitly when the block stops executing and 'manually' closing the connections could kinda bloat the codebase with unnecessary code. But shouldn't I do so in order to make by code as readable and as easy understandable as possible, while also preventing several possible issues during run time? Also, if I would do, would it be enough to unset() my database object?

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  • Google I/O 2012 - From Weekend Hack to Funded Startup - How to Build Your Team and Raise Money

    Google I/O 2012 - From Weekend Hack to Funded Startup - How to Build Your Team and Raise Money Naval Ravikant, Rich Miner, Kevin Rose Have an idea and want to start a company? Learn how to attract investors, and what they want to see before writing a check. Hear from entrepreneurs who have raised money and VCs who have funded them. For all I/O 2012 sessions, go to developers.google.com From: GoogleDevelopers Views: 0 0 ratings Time: 01:00:30 More in Science & Technology

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  • Using runtime generic type reflection to build a smarter DAO

    - by kerry
    Have you ever wished you could get the runtime type of your generic class? I wonder why they didn’t put this in the language. It is possible, however, with reflection: Consider a data access object (DAO) (note: I had to use brackets b/c the arrows were messing with wordpress): public interface Identifiable { public Long getId(); } public interface Dao { public T findById(Long id); public void save(T obj); public void delete(T obj); } Using reflection, we can create a DAO implementation base class, HibernateDao, that will work for any object: import java.lang.reflect.Field; import java.lang.reflect.ParameterizedType; public class HibernateDao implements Dao { private final Class clazz; public HibernateDao(Session session) { // the magic ParameterizedType parameterizedType = (ParameterizedType) clazz.getGenericSuperclass(); return (Class) parameterizedType.getActualTypeArguments()[0]; } public T findById(Long id) { return session.get(clazz, id); } public void save(T obj) { session.saveOrUpdate(obj); } public void delete(T obj) { session.delete(obj); } } Then, all we have to do is extend from the class: public class BookDaoHibernateImpl extends HibernateDao { }

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  • bad practice to create a print friendly page to remove the use of pdfs?

    - by Phil
    the company I work for has a one page invoice that uses the library tcpdf. they wanted to do some design changes that I found are just incredibly difficult for setting up in .pdf format. using html/css I could easily create the page and have it print very nicely, but I have a feeling that I am over looking something. is it a good practice to set up a page just for printing? and if not, is it at least better than putting out a ugly .pdf? I could also use the CSS inline so that if they wanted to download it and open it they could.

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  • Google I/O 2012 - Spatial Data Visualization

    Google I/O 2012 - Spatial Data Visualization Brendan Kenny, Enoch Lau Maps were among the first data visualizations, but they can also provide the backdrop for visualizing your own spatial data. In this session, we'll take a voyage through the world of map based data visualization, arming you with the tools you need to most effectively bring your data to life on a map using the Maps API v3. For all I/O 2012 sessions, go to developers.google.com From: GoogleDevelopers Views: 1053 26 ratings Time: 01:00:17 More in Science & Technology

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