cumm-cu113 0.2.1

CUda Matrix Multiply library

cumm

CUda Matrix Multiply library.

cumm is developed during learning of CUTLASS, which use too much c++ template and make code unmaintainable. So I develop pccm, use python as meta programming language, to replace c++ template meta programming. Now pccm become a foundational framework of cumm and my other c++ project such as spconv. cumm also contains a python asyncio-based gemm simulator that share same meta program with CUDA code, enable gemm visualization and easy debug experience.

Install

Prebuilt

We offer python 3.7-3.10 and cuda 10.2/11.1/11.3/11.4 prebuilt binaries for linux (manylinux).

We offer python 3.7-3.10 and cuda 10.2/11.1/11.3/11.4 prebuilt binaries for windows 10/11.

We will offer prebuilts for CUDA versions supported by latest pytorch release. For example, pytorch 1.9 support cuda 10.2 and 11.1, so we support them too.

pip install cumm-cu102 for CUDA 10.2

pip install cumm-cu111 for CUDA 11.1

pip install cumm-cu113 for CUDA 11.3

pip install cumm-cu114 for CUDA 11.4

Build from source

Linux

1. install build-essential, install CUDA
2. run export CUMM_DISABLE_JIT="1"
3. run python setup.py install/pip install -e ./python setup.py bdist_wheel+pip install dists/xxx.whl

Windows 10/11

1. install visual studio 2019 or newer. make sure C++ development package is installed. install CUDA
2. set powershell script execution policy
3. start a new powershell, run tools/msvc_setup.ps1
4. run $Env:CUMM_DISABLE_JIT = "1"
5. run python setup.py install/pip install -e ./python setup.py bdist_wheel+pip install dists/xxx.whl

Note

The work is done when the author is an employee at Tusimple.