dlprimitives
pytorch_dlprim
dlprimitives | pytorch_dlprim | |
---|---|---|
7 | 3 | |
156 | 207 | |
- | - | |
3.8 | 5.9 | |
5 months ago | about 1 month ago | |
C++ | C++ | |
MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
dlprimitives
- Dlprimitives: Deep Learning Primitives and Mini-Framework for OpenCL
-
[P] OpenCL backend for PyTorch - progress works with mainstream pytorch
I'm working on PyTorch OpenCL backend based on dlprimitives core library. It exists for a while but until now it required building custom pytorch version.
-
[P] DLPrimitives - wondering about best development direction
BTW Performance numbers: https://github.com/artyom-beilis/dlprimitives/blob/master/docs/benchmarks/benchmarks-gtx1080.md (I just added below TF2 that is missing in docs)
-
[P] DLPrimitives - an OpenCL miro-framework and inference library
Full benchmarks can be found there: https://github.com/artyom-beilis/dlprimitives/blob/master/docs/summary.md
- [P] OpenCL Deep Learning Primitives Library
pytorch_dlprim
-
Linus Tech Tips: "China doesn't want me to have this GPU [Moore Threads MTT S80]" (Linus Tech Tips Reviews the Moore Threads MTT S80 GPU)
I know PyTorch supports OpenCL nows and you can do training with it as well. See here. Never try it myself.
-
[P] OpenCL backend for PyTorch - progress works with mainstream pytorch
I'm working on PyTorch OpenCL backend based on dlprimitives core library. It exists for a while but until now it required building custom pytorch version.
- [P] Progress with OpenCL backend for pytorch
What are some alternatives?
tensorflow-opencl - OpenCL support for TensorFlow
oneDNN - oneAPI Deep Neural Network Library (oneDNN)
plaidml - PlaidML is a framework for making deep learning work everywhere.
mace - MACE is a deep learning inference framework optimized for mobile heterogeneous computing platforms.
AdaptiveCpp - Implementation of SYCL and C++ standard parallelism for CPUs and GPUs from all vendors: The independent, community-driven compiler for C++-based heterogeneous programming models. Lets applications adapt themselves to all the hardware in the system - even at runtime!
Boost.Compute - A C++ GPU Computing Library for OpenCL
pytorch-coriander - OpenCL build of pytorch - (in-progress, not useable)
FluidX3D - The fastest and most memory efficient lattice Boltzmann CFD software, running on all GPUs via OpenCL.
ParallelReductionsBenchmark - Thrust, CUB, TBB, AVX2, CUDA, OpenCL, OpenMP, SyCL - all it takes to sum a lot of numbers fast!
OpenCL-Guide - OpenCL Guide