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initial support blackwell #747

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6 changes: 3 additions & 3 deletions .github/workflows/release_wheel.yml
Original file line number Diff line number Diff line change
Expand Up @@ -18,16 +18,16 @@ on:
# required: true

env:
TORCH_CUDA_ARCH_LIST: "7.5 8.0 8.9 9.0+PTX"
TORCH_CUDA_ARCH_LIST: "7.5 8.0 8.9 9.0 10.0 12.0+PTX"

jobs:
build:
strategy:
fail-fast: false
matrix:
python: ["3.8", "3.9", "3.10", "3.11", "3.12"]
cuda: ["11.8", "12.1", "12.4"]
torch: ["2.3", "2.4", "2.5"]
cuda: ["11.8", "12.1", "12.4", "12.6", "12.8"]
torch: ["2.3", "2.4", "2.5", "2.6"]
exclude: # for cuda 12.4, we only support torch 2.4+
- cuda: "12.4"
torch: "2.2"
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2 changes: 1 addition & 1 deletion 3rdparty/cutlass
Submodule cutlass updated 2034 files
2 changes: 1 addition & 1 deletion cmake/config.cmake
Original file line number Diff line number Diff line change
Expand Up @@ -35,7 +35,7 @@ set(FLASHINFER_GEN_MASK_MODES 0 1 2)
# "native" is a special value for CMAKE_CUDA_ARCHITECTURES which means use the
# architectures of the host's GPU. it's new in CMake 3.24, if you are using an
# older of CMake or you want to use a different value, you can set its value
# here. Supported CUDA architectures include 80;86;89;90
# here. Supported CUDA architctures include 80;86;89;90;100;120
# NOTE(Zihao): using "native" might be slow because whenever compile a cuda file
# with `-arch=native`, nvcc will spawn a `__nvcc_device_query` process to get
# the architecture of the host's GPU, which could stall the compilation process.
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4 changes: 2 additions & 2 deletions docs/installation.rst
Original file line number Diff line number Diff line change
Expand Up @@ -155,7 +155,7 @@ You can follow the steps below to install FlashInfer from source code:
.. code-block:: bash

cd flashinfer
TORCH_CUDA_ARCH_LIST="7.5 8.0 8.9 9.0a" FLASHINFER_ENABLE_AOT=1 pip install --no-build-isolation --verbose --editable .
TORCH_CUDA_ARCH_LIST="7.5 8.0 8.9 9.0a 10.0 12.0 12.0a" FLASHINFER_ENABLE_AOT=1 pip install --no-build-isolation --verbose --editable .

5. Create FlashInfer distributions (optional):

Expand All @@ -182,7 +182,7 @@ You can follow the steps below to install FlashInfer from source code:
.. code-block:: bash

cd flashinfer
TORCH_CUDA_ARCH_LIST="7.5 8.0 8.9 9.0a" FLASHINFER_ENABLE_AOT=1 python -m build --no-isolation --wheel
TORCH_CUDA_ARCH_LIST="7.5 8.0 8.9 9.0a 10.0 12.0 12.0a" FLASHINFER_ENABLE_AOT=1 python -m build --no-isolation --wheel
ls -la dist/

C++ API
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