Vortex: OpenCL Compatible RISC-V GPGPU

https://arxiv.org/abs/2002.12151

by pjmlp • 6 years ago

115 27 6 years ago

arxiv.org

muizelaar• 6 years ago

The code is maybe at: https://github.com/felsabbagh3/Vortex

algorithm314• 6 years ago

An other RISCV GPU from Think Silicon https://think-silicon.com/2019/12/02/think-silicon-demonstra...

lwb• 6 years ago

Anyone here use OpenCL for their day job? Practically speaking, what are the use cases for it in a corporate environment?

sjmulder• 6 years ago

I’ve been exploring it for use for financial calculations that are ‘embarrassingly parallel’. It’s much faster alright but people here aren’t trained in data oriented programming. Might end up writing some generic accelerated building blocks for use from VBA.

lmeyerov2• 6 years ago

We abandoned it due to lack of ecosystem support. We originally picked it for general ETL / analytics / preprocessing data viz when opencl vs. nvidia for commodity data parallel hardware ( = GPU ) was unclear, and as a long option in case FGPAs would ultimately make sense. But the CUDA software stack's community + Nvidia investments eventually converted us.

Interestingly, we now exclusively use high-level data parallel abstractions like RAPIDS dataframes, so if there was say a Modin->risc-v path, wouldn't be too heavy a lift to port most of our stack. (Though, as is, little reason to.)

zozbot2342• 6 years ago

The ecosystem seems to be moving to Vulkan-based compute these days. That's more aligned to the hardware than plain old OpenCL, so performance should be improved.

bubblethink• 6 years ago

It's like CUDA, but not owned by NVIDIA. AMD's entire ROCM stack is based on OpenCL. That means that if you run tenserflow on amd gpus, you are using OpenCL. By corporate environment, if you mean day to day IT, probably none. It's useful for high performance and parallel code.

pjmlp2• 6 years ago

You got it wrong, it is like CUDA but only supports C, has lousier debugging tools, and buggy drivers.

Yes it does support C++ and finally has its own bytecode format for heterogeneous programming, but unless the card is OpenCL 2.2, it is back to my first paragraph.

rrss• 6 years ago

Pretty sure the rocm backend for tensorflow uses hip, not OpenCL, and hip is basically just AMD's implementation of cuda.

I don't think it's accurate to say that the "entire ROCM stack is based on OpenCL." The rocm stack supports OpenCL, but it also supports hip, which is what AMD chose to use to implement many of the new libraries in the rocm platform (rocBLAS, rocFFT, rccl; replacing cuBLAS, cuFFT, nccl)

FWIW, rocm also doesn't support OpenCL 2.0.

nl• 6 years ago

ROCM isn't OpenCL based.

Ono-Sendai2• 6 years ago

Yes, we use it for Indigo Renderer (https://www.indigorenderer.com/) and Chaotica Fractals (https://www.chaoticafractals.com/). It allows cross-platform (Windows, Mac, Linux) execution on GPUs.

boulos• 6 years ago

Vlado mentioned at SIGGRAPH, that they basically gave up and has gone from OpenCL => CUDA => "let OptiX handle it" => "OptiX7 w/ RTX". Do you have a CUDA and/or RTX comparison?

P.S. It's awesome you're still working on Indigo!

wyldfire• 6 years ago

If you have an HPC workload it can make sense. Lots and lots of software work is I/O bound and doesn't do a whole heckuva lot of computation.

I used to use OpenCL at work a lot.

Awtem• 6 years ago

Sadly, OpenCL (alongside OpenGL) are already deprecated on Mac...

pjmlp2• 6 years ago

Currently none.

Android uses its own dialect, RenderScript.

iOS had OpenCL, but since Metal got introduced, Metal Shaders are much better.

On Windows I used C++AMP for a while, now I just make use of Java/.NET libraries that plug into CUDA.

OpenCL biggest mistake was focusing on C only instead of opening the programming model to other languages.

SPIR and SYS-CL came too late into the game.

fulafel2• 6 years ago

Blender and Darktable use it at least. Also commercial Mac apps like Photoshop, Premiere etc.

It's emitted by a bunch of compiler backends (eg Futhark).

ML and computer vision toolkits support it (eg PyTorch, OpenCL etc).

Not sure what you mean by corporate environments but the suits probably mostly use Excel and calc.exe :)

kitd• 6 years ago

Tbf, Excel making use of OpenCL kind of makes sense :)

MeteOzturk2• 6 years ago

I am curious how RISC-V GPGPU development would affect Nvidia’s support for the platform. So far they seemed to be supportive. They’ve contributed NVDLA. They’re a member of the foundation. It’s not far-fetched to think a Jetson with high performance RISC cores is already in development. I hope they won’t back out if they deem a strong edge platform competitor is not in their best interest.

zozbot2342• 6 years ago

nVidia are not using RISC-V for their "high-performance" GPGPU cores. Their interest in RISC-V is only for support cores, so GPGPU support is neither here nor there.

MeteOzturk2• 6 years ago

What Nvidia brings to the table with both the Jetson line and the Tegra line is precisely those GPGPU's. The ARM parts are pretty standard I believe. What I meant was if there was enough interest and development around an open-source architecture for GPGPU's and Neural processing it would have the potential to become a competitor to Nvidia's offering. I am confident it would take years to become a worthy competitor in the desktop and server markets. Edge and portable devices I am not so sure.

jarrell_mark• 6 years ago

Deep Learning could in theory run on this using Intel PlaidML's Keras implementation in OpenCL https://github.com/plaidml/plaidml

fulafel2• 6 years ago

Isn't OpenCL just a c-like language that can run/be impemented on most things, what about the RISC-V architecture prevented running eg POCL?

edit: seems the paper is mostly about adding SIMT support to RISC-V, proably the answer to the above is that it RISC-V can run OpenCL even without the extension.

Vortex: OpenCL Compatible RISC-V GPGPU

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