5 ms·

That's not exactly true once you have to deal with vector extensions like AVX-512. It's quite a pain to write by hand (C intrinsics) and many of the ways to abs

That's not exactly true once you have to deal with vector extensions like AVX-512. It's quite a pain to write by hand (C intrinsics) and many of the ways to abstract it away end up giving you a GPU-like programming model (eg. Intel ISPC). Plus, this has largely been tried before with Xeon Phi and it didn't end so well. Huge vector units like AVX-512 are mainly useful for workloads that need huge amounts of RAM that you just can't get with a GPU, or for workloads that are very latency sensitive and incompatible with GPU task scheduling because they are in some other CPU-bound code.

jiggawatts 6y ago
> It's quite a pain to write by hand And we all know that autovectorisation is hit-and-miss at best. I wonder if there will be a new C-like language that has portable SIMD-like capabilities in the same sense that "C is a portable assembly language".
- mmozeiko 6y ago
  There is - Intel SPMD Program Compiler. https://ispc.github.io/ https://ispc.github.io/
  - benibela 6y ago
    But does that work on AMD ?
- Fronzie 6y ago
  Another one is SyCL: https://www.khronos.org/sycl/ https://www.khronos.org/sycl/ the SIMD part is OpenCL, SyCL provides scheduling/memory transfer on top.
- DeathArrow 6y ago
  >The first observation is that in modern compilers, the resulting performance from auto-vectorization optimization is still far from the architectural peak performance. https://dl.acm.org/doi/fullHtml/10.1145/3356842 https://dl.acm.org/doi/fullHtml/10.1145/3356842 Maybe we can get get more benefits if we invest more resources in optimizing compilers than in inventing yet another Javascript framework?
imtringued 6y ago
>Huge vector units like AVX-512 are mainly useful for workloads that need huge amounts of RAM that you just can't get with a GPU, or for workloads that are very latency sensitive and incompatible with GPU task scheduling because they are in some other CPU-bound code. There are a lot of tasks that a GPU can do faster than a CPU but it would require batching a large amount of work before you can gain a speedup. EYPC CPUs do not suffer that limitation. If all you have is an array with 4 elements you can straight up run the vector instructions and then immediately switch back to scalar code. Meanwhile with a GPU you probably need at least an array with 10000 elements or more.

jiggawatts 6y ago

> It's quite a pain to write by hand And we all know that autovectorisation is hit-and-miss at best. I wonder if there will be a new C-like language that has portable SIMD-like capabilities in the same sense that "C is a portable assembly language".

mmozeiko 6y ago
There is - Intel SPMD Program Compiler. https://ispc.github.io/ https://ispc.github.io/
- benibela 6y ago
  But does that work on AMD ?
Fronzie 6y ago
Another one is SyCL: https://www.khronos.org/sycl/ https://www.khronos.org/sycl/ the SIMD part is OpenCL, SyCL provides scheduling/memory transfer on top.
DeathArrow 6y ago
>The first observation is that in modern compilers, the resulting performance from auto-vectorization optimization is still far from the architectural peak performance. https://dl.acm.org/doi/fullHtml/10.1145/3356842 https://dl.acm.org/doi/fullHtml/10.1145/3356842 Maybe we can get get more benefits if we invest more resources in optimizing compilers than in inventing yet another Javascript framework?

imtringued 6y ago

>Huge vector units like AVX-512 are mainly useful for workloads that need huge amounts of RAM that you just can't get with a GPU, or for workloads that are very latency sensitive and incompatible with GPU task scheduling because they are in some other CPU-bound code. There are a lot of tasks that a GPU can do faster than a CPU but it would require batching a large amount of work before you can gain a speedup. EYPC CPUs do not suffer that limitation. If all you have is an array with 4 elements you can straight up run the vector instructions and then immediately switch back to scalar code. Meanwhile with a GPU you probably need at least an array with 10000 elements or more.