blocks|key|993733|text|嗯，OpenCL的主要优势是它不仅仅局限于显卡。您可以使用您的多核CPU，显卡和潜在的任何数量的其他硬件加速设备(DSP等)，所有这些都来自同一个程序。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|993734|我不确定DirectCompute是否允许这种自由。|993735|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|F|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|G|8|@]|9|@]|A|$]]|$1|D|3|-4|5|6|7|H|8|@]|9|@]|A|$]]]|E|$]]

Well the major advantage of OpenCL is that it is not just limited to graphics cards. You can make use of your multicore CPU, Graphics Card and potentially any number of other hardware acceleration devices (DSPs etc) all from the same program.

I'm not sure if DirectCompute allows that freedom.

blocks|key|993769|text|对于编码器来说，最大的区别可能是DirectCompute是由类似于HLSL的语言编程的，而OpenCL是通过类似C的语言编程的。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|993770|另一个需要考虑的区别是，一般来说，对于商品级GPU，DirectX支持比Windows上的OpenGL支持更好(更快，错误更少)。这可能会转化为对DirectCompute更稳定的支持，但实际上，这只是一种猜测。|993771|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|F|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|G|8|@]|9|@]|A|$]]|$1|D|3|-4|5|6|7|H|8|@]|9|@]|A|$]]]|E|$]]

Probably the biggest difference for a coder is that DirectCompute is programmed by a language which is similar to HLSL, and OpenCL is programmed via a C-like language. 

Another difference to consider is that, generally, for commodity level GPUs, the DirectX support is better (faster and less buggy) than OpenGL support on Windows. This may translate to more stable support for DirectCompute, but really, this is just speculation.

blocks|key|1208183|text|我使用OpenCL是因为我可以很容易地将我的应用程序移植到Linux上，但是使用DirectCompute就不可能了。我还认为OpenCL实现的性能将随着时间的推移而提高(它与NVidia卡的CUDA处于相同的水平)，并且(驱动程序)错误也将随着时间的推移而消除。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1208184|entityMap^0|0^^$0|@$1|2|3|4|5|6|7|D|8|@]|9|@]|A|$]]|$1|B|3|-4|5|6|7|E|8|@]|9|@]|A|$]]]|C|$]]

I use OpenCL because i can easily port my App to Linux but with DirectCompute this is not possible.
I think also that the performance of the OpenCL implementation will increase with time (that it comes at the same Level like CUDA for NVidia Cards) and also that the (driver)bugs will (hopefully ;) ) be eliminated with time.

blocks|key|1208215|text|OpenCL的跨平台性不仅仅是一个细节，因为主机代码(调用OpenCL应用程序接口并提交内核的代码)本身也可以是跨平台的(参见link+text，link+text...)。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|1208216|编写一次，在任何地方的任何GPGPU上运行。|1208217|除此之外，随着Visual+Studio的ATI+Stream插件、包含大量示例的NVidia和ATI+SDK等，OpenCL工具真的变得越来越好了。|1208218|entityMap|0|LINK|mutability|MUTABLE|url|http://code.google.com/p/javacl/|1|http://mathema.tician.de/software/pyopencl^0|1R|9|0|21|9|1|0|0|0^^$0|@$1|2|3|4|5|6|7|R|8|@]|9|@$A|S|B|T|1|U]|$A|V|B|W|1|X]]|C|$]]|$1|D|3|E|5|6|7|Y|8|@]|9|@]|C|$]]|$1|F|3|G|5|6|7|Z|8|@]|9|@]|C|$]]|$1|H|3|-4|5|6|7|10|8|@]|9|@]|C|$]]]|I|$J|$5|K|L|M|C|$N|O]]|P|$5|K|L|M|C|$N|Q]]]]

The OpenCL cross-platform-ness is not just a detail, as the host code (the one calling the OpenCL API and submitting kernels) can itself be cross-platform (see <a href="http://code.google.com/p/javacl/" rel="noreferrer" title="JavaCL">link text</a>, <a href="http://mathema.tician.de/software/pyopencl" rel="noreferrer" title="PyOpenCL">link text</a>...).

Write once, run on any GPGPU, anywhere.

Otherwise the OpenCL tooling is really getting better, with an ATI Stream plugin for Visual Studio, the NVidia &amp; ATI SDKs that contains tons of samples, etc...

blocks|key|1208255|text|现在的另一个选择是C%2B%2B+AMP，它为您提供了现代的C%2B%2B语法，而不需要单独的编译器，同时仍然保留了硬件的可移植性。请点击此处的链接获取更多信息，并随时发布您的问题：http://blogs.msdn.com/b/nativeconcurrency/archive/2011/09/13/c-amp-in-a-nutshell.aspx|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|1208256|entityMap|0|LINK|mutability|MUTABLE|url|http://blogs.msdn.com/b/nativeconcurrency/archive/2011/09/13/c-amp-in-a-nutshell.aspx^0|2B|2D|0|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@$A|M|B|N|1|O]]|C|$]]|$1|D|3|-4|5|6|7|P|8|@]|9|@]|C|$]]]|E|$F|$5|G|H|I|C|$J|K]]]]

Another option now is C++ AMP which gives you modern C++ syntax without a need for a seperate compiler while still preserving hardware portability. Please follow links from here for more info and feel free to post questions as you have them: <a href="http://blogs.msdn.com/b/nativeconcurrency/archive/2011/09/13/c-amp-in-a-nutshell.aspx" rel="nofollow">http://blogs.msdn.com/b/nativeconcurrency/archive/2011/09/13/c-amp-in-a-nutshell.aspx</a>

I'm looking for comparisons between <a href="http://en.wikipedia.org/wiki/OpenCL" rel="nofollow noreferrer">OpenCL</a> and <a href="http://en.wikipedia.org/wiki/DirectCompute" rel="nofollow noreferrer">DirectCompute</a>, but I haven't found anything. OpenCL's advantages of being cross-platform and having a wider range of supported GPUs don't matter to me. I'm fine with coding on Windows against DX11 GPUs only. Assuming that, what are the pros and cons of each API?

I know <a href="https://stackoverflow.com/questions/2915350/directcompute-versus-opencl-for-gpu-programming">this question was raised before</a>, but I'm looking for more details.

I'm not interested in CUDA, since I don't want to restrict myself to only Nvidia hardware.

OpenCL vs. DirectCompute?

翻译质量差，导致语言生硬或混乱。

没有提供实际的解决方法或示例。

解答不清晰，无法理解或解决问题。

页面排版不美观，阅读体验差。

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我正在寻找和之间的比较，但我没有找到任何东西。OpenCL跨平台和支持更多GPU的优势对我来说无关紧要。我可以在Windows上使用DX11 GPU编码。假设这样，每种API的优缺点是什么？我知道，但我想知道更多细节。我对CUDA不感兴趣，因为我不想把自己限制在Nvidia硬件上。

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