DirectCompute from an OpenCL and CUDA perspective
Currently, most of my GPGPU experience is with OpenCL and CUDA. I have recently been looking at DirectCompute as another IHV-neutral API besides OpenCL. I have tried porting some of my OpenCL code to DirectCompute to gain experience. Here are some notes, in no particular order, from the perspective of writing compute code which has no graphics component:
1. Basic programming paradigm is similar to OpenCL 1.2 and basic CUDA. You have threads organized into thread groups, you have access to local memory/on-chip shared memory and synchronization etc is fairly similar as well.
2. However, it is far behind the functionality in CUDA 5.x and OpenCL 2.0. For example, there is no support for dynamic parallelism. It is likely that Microsoft is considering adding these features, but with no public roadmap it is difficult to say anything. DirectCompute has not really evolved much since it started shipping in Windows 7 in late 2009 (i.e. almost 4 years ago).
3. No support for multiple command queues per context. CUDA has streams and OpenCL has the ability to create multiple command queues per context, but I think there is only one implicit command queue per device context in DirectCompute. I think this will be a problem under many compute scenarios.
4. Shared memory support is very limited. D3D 11.2 introduces some features that take one step towards shared memory, but it is not fully there yet. On OpenCL, we already have decent shared memory support under OpenCL 1.2 on Intel platforms. OpenCL 2.0 is going to bring proper shared memory support on many platforms.
5. Double-precision support in HLSL is limited. There are no trigonometric functions or exponential functions. On Windows 7, you don’t even get double-precision FMA or divide in the shader bytecode. You can potentially the missing functions yourself but a serious compute API should include them. Using Microsoft’s C++ AMP instead of using DirectCompute takes care of some of this on Windows 8.
6. Vendor tools are geared for games and graphics applications. Profilers from various vendors all provide “per frame” analysis, which is useful for graphics applications but useless for pure compute scenarios. OpenCL and CUDA tools are geared for compute and are getting pretty good. I think this will again be different for C++ AMP.
7. Driver quality for DirectCompute is far more consistent across vendors compared to OpenCL. With OpenCL, it is not uncommon to run into frustrating bugs in various drivers. Also, sometimes driver writers interpret the OpenCL spec quite “creatively” which is very frustrating and often requires multiple codepaths even in host API code. DirectCompute drivers are far more robust, less buggy and the program behavior is usually what you expect across all vendors.
8. Hardware-vendor independant shader bytecode is great to have in DirectCompute. OpenCL SPIR will tackle this but it is not yet implemented.
9. Thread-group size is compile time constant in DirectCompute. In OpenCL and CUDA, you can delay specifying the group size until dispatch and can dispatch it with a different group size in every invocation. Even OpenGL compute shaders are getting this ability with a new extension (GL_arb_compute_variable_group_size).
10. Documentation is not that great. I guess I am used to downloading OpenCL specs directly and reading them while MSDN is a bit harder to navigate. For example, Direct3D 11.2 docs are essentially diffs over D3D 11.1 which makes it hard to get the complete up-to-date picture in one place. Vendor documentation is also woefully inadequate on many DirectCompute related things. For example, just trying to find out which GPUs from any vendor supports all double-precision instructions and which doesn’t is hard. Vendors also don’t seem to bother providing detailed optimization guides for DirectCompute.
My experience is limited however, and it is likely I have gotten some things wrong. If you have any corrections to offer, please let me know
Overall I feel that if your app is not already using Direct3D, you probably should not use DirectCompute. You are probably better off choosing OpenCL for many compute scenarios. OpenCL has some technical advantages over DirectCompute as outlined above, is a more future-proof and platform-independent path and has much better documentation and tooling support today than DirectCompute for pure compute scenarios. Alternately, if you want to stick to Microsoft stack, then you are probably better off choosing C++ AMP over DirectCompute.