forked from jiuyuan/InfiniTensor
7f6aec6c17
* fix(dist): 改善分布式脚本,只打印绝对误差 * feat(dist): 增加可导出onnx的pytorch运行脚本 * feat(front): 增加对Y值为-inf的where算子的图优化 * feat(kernel): 对b为常数的pow和div算子进行特判优化 * fix(front): 消除前端对global output形状信息的依赖,分布式脚本删除不必要的shape infer * feat(kernel): 针对matmul中bias为行向量时的expand操作的特化优化 * fix(kernel): 删除div pow const中不必要的同步 * Update expand.cu * fix: fix comments --------- Co-authored-by: Haojie Wang <haojie0429@gmail.com> Co-authored-by: Derui Yang <ydrml@hotmail.com> |
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.github/workflows | ||
3rd-party | ||
cmake | ||
docs | ||
examples | ||
include | ||
proto | ||
pyinfinitensor | ||
python | ||
scripts | ||
src | ||
test | ||
.clang-format | ||
.cmake-format.json | ||
.gitignore | ||
.gitmodules | ||
CHANGELOG.md | ||
CMakeLists.txt | ||
LICENSE | ||
Makefile | ||
README.md | ||
README_CN.md | ||
env.sh |
README.md
InfiniTensor
InfiniTensor is a high-performance inference engine tailored for GPUs and AI accelerators. Its design focuses on effective deployment and swift academic validation.
Get started
Make Commands
make
/make build
: Builds the project;make install-python
: Builds the project then install the python frontend;make test-cpp
: Builds the project then run cpp unit tests;make test-onnx
: Run python unit tests;
- Sets env:
TEST=OFF
to accelerate compiling.- Sets env:
CUDA=ON
to enable cuda.- Sets env:
BANG=ON
to enable bang.
CMake Options
There are several configurable CMake options, see the CMakeLists.txt file.
- If
USE_BACKTRACE
isON
,libdw-dev
have to be installed. See the README of backward-cpp for details. - If
USE_PROTOBUF
isON
,protobuf
have to be installed. See the README of protobuf for details. - If
USE_CUDA
isON
,cuda
have to be installed.
Roadmap
- RefactorGraph is a newly designed AI framework that is set to replace the current main branch.
- EinNet is going to be merged into the main branch.
- Integration of PET, a tensor program optimizer supporting partially equivalent transformations.
- Supported hardware
- ✔ NVIDIA GPU
- ✔ Cambricon MLU
- ✔ Kunlunxin XPU
- ⬜ Ascend NPU
Contributor Guide
InfiniTensor development is based on the pull request on Github. Before requesting for merging, a PR should satisfy the following requirements
- Pass all tests.
- Now CI on Github will test everything that can be tested in the ci environment, including code format. So, script
test/script/clang_format_inplace.sh
is for formatting all code. - Contributors should run
ctest
manually and copy its output to the PR. Use fenced code blocks (triple backquotes, i.e.,```
) to avoid referencing in Github. Otherwise,#
in the output is interpreted as a Github reference. Do not directly paste the ctest output in commit messages either for the same reason.
- Now CI on Github will test everything that can be tested in the ci environment, including code format. So, script
- Receive at least one approval from reviewers.
- PR title should be concise since it is going to be the commit message in the main branch after merging and squashing.
Reference
Please cite EinNet or PET in your publications if it helps your research:
@article{zheng2023einnet,
title={EINNET: Optimizing Tensor Programs with Derivation-Based Transformations},
author={Zheng, Liyan and Wang, Haojie and Zhai, Jidong and Hu, Muyan and Ma, Zixuan and Wang, Tuowei and Huang, Shuhong and Miao, Xupeng and Tang, Shizhi and Huang, Kezhao and Jia, Zhihao},
booktitle={17th USENIX Symposium on Operating Systems Design and Implementation (OSDI 23)},
pages={739--755},
year={2023}
}
@inproceedings{wang2021pet,
title={PET: Optimizing tensor programs with partially equivalent transformations and automated corrections},
author={Wang, Haojie and Zhai, Jidong and Gao, Mingyu and Ma, Zixuan and Tang, Shizhi and Zheng, Liyan and Li, Yuanzhi and Rong, Kaiyuan and Chen, Yuanyong and Jia, Zhihao},
booktitle={15th USENIX Symposium on Operating Systems Design and Implementation (OSDI 21)},
pages={37--54},
year={2021}
}