No project description provided
Project description
FBGEMM_GPU
FBGEMM_GPU (FBGEMM GPU Kernels Library) is a collection of high-performance PyTorch GPU operator libraries for training and inference. The library provides efficient table batched embedding bag, data layout transformation, and quantization supports.
FBGEMM_GPU is currently tested with CUDA 12.1 and 11.8 in CI, and with PyTorch packages (2.1+) that are built against those CUDA versions.
See the full Documentation for more information on building, installing, and developing with FBGEMM_GPU, as well as the most up-to-date support matrix for this library.
Join the FBGEMM_GPU Community
For questions, support, news updates, or feature requests, please feel free to:
- File a ticket in GitHub Issues
- Post a discussion in GitHub Discussions
- Reach out to us on the
#fbgemm
channel in PyTorch Slack
For contributions, please see the CONTRIBUTING
file for
ways to help out.
License
FBGEMM_GPU is BSD licensed, as found in the LICENSE
file.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distributions
Built Distributions
Hashes for fbgemm_gpu_cpu-0.7.0-cp312-cp312-manylinux2014_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 93ad6e7fc9e4b2046e220ae4884817f0b8f74077e7d7c4800c4ecc1aced7e917 |
|
MD5 | 11e8cef3048b2d622a21402d5ad2fd19 |
|
BLAKE2b-256 | 58cac5fe6f2e9856bda98c92e2e4c9e03c48fa7b6510cc9b79ab105507d60867 |
Hashes for fbgemm_gpu_cpu-0.7.0-cp312-cp312-manylinux2014_aarch64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | cbb2dbfe5c6d6f6cbcab8d3e3f2470e6efb14d0b466dc4b3b00c8def4a193e05 |
|
MD5 | 034c038e6a1421ce187cf5302cd0cafd |
|
BLAKE2b-256 | 22ec3703af0238ca817e20ba298206129494ea3c3c6198354395e04c6a6fd562 |
Hashes for fbgemm_gpu_cpu-0.7.0-cp311-cp311-manylinux2014_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | d57f2fdc300ccff0d95d537068cfc1f04ef3c6ca5b63450ac7b51aa6efcc120f |
|
MD5 | 03057bec8d56ed929bcd2ea26c443de5 |
|
BLAKE2b-256 | 9bb86766c6114cd07877de1f8d82019193a55b417e5326317afdb56c94a77905 |
Hashes for fbgemm_gpu_cpu-0.7.0-cp311-cp311-manylinux2014_aarch64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | f640b9a0aa90cb68fb9032dddee9f0830882b566f524633975a76c2a9c6872ef |
|
MD5 | dd59c4eb1d3151e4de1e69ebe84856a7 |
|
BLAKE2b-256 | 99ed8e40d9eda73eeb9cec1892fb28bb49423572504d1cca85e0e858119d006c |
Hashes for fbgemm_gpu_cpu-0.7.0-cp310-cp310-manylinux2014_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 47aaf16689f35e82644e465d648f5145188ba6d2f265aa13dea84ce92136b53e |
|
MD5 | 10c0fba9dfbfee0c5523880eb17543f4 |
|
BLAKE2b-256 | 3abe14c8bfb8ea9ce2983e965d03813d5698d0ef90ece44a5a74a38636643feb |
Hashes for fbgemm_gpu_cpu-0.7.0-cp310-cp310-manylinux2014_aarch64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | fe120deaaa5cdb10c434fccf9ad31e16738061e1cc5c7e4c67bec1e4d6fb0ff0 |
|
MD5 | 719f10486417af7d9d98188c10786553 |
|
BLAKE2b-256 | 99cef61020cfe9aa5dafd4a44f296a20ad4195acc201629c007d692c0e382200 |
Hashes for fbgemm_gpu_cpu-0.7.0-cp39-cp39-manylinux2014_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 46b4a42d063e5faeb354bc0a4076e06d324ff9921c8ca97e4cbfec9143580eee |
|
MD5 | 3e779276314dc8402e7c21366ac88898 |
|
BLAKE2b-256 | d03fc7b017d18001a78a56de13e96fddc5beac40246cf2f5dd3c59ea63e421fd |
Hashes for fbgemm_gpu_cpu-0.7.0-cp39-cp39-manylinux2014_aarch64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | af835b4d64419ded1cc7c7ce25d1f28a4314396c75a379f37acff47b1b022e61 |
|
MD5 | 9ffc89dd50644e3482983a9a6cffb93d |
|
BLAKE2b-256 | 27c3d0a5a0eae5e08ce90b7ef5ff1441e4646e30f08aba07efc48da704244008 |
Hashes for fbgemm_gpu_cpu-0.7.0-cp38-cp38-manylinux2014_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | cca989fa5b563ba8bb97bfe8dc5d6424edcd68bf82ffad6b4ae77479745c0fe0 |
|
MD5 | 6c0b7fc40b6a396aa624c58040e9e374 |
|
BLAKE2b-256 | 6d148fb3606ee94d252615e44a8f94aad86af17ee439ed07078b38a67e294ba0 |
Hashes for fbgemm_gpu_cpu-0.7.0-cp38-cp38-manylinux2014_aarch64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 73edc88cd3fb9b19af69c8bf423e5c49f396447e54c205231921ec9747b75753 |
|
MD5 | e96d36d24017d0179b6c6c26c71f1dc1 |
|
BLAKE2b-256 | 675eade040680f1eec07622732ab0c0089defab5760944704841489d8304f05c |