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  • Installation Instructions — FBGEMM 1. 4. 0 documentation
    Set Up the CUDA Docker Container and Conda Environment It is recommended, though not required, to install and run FBGEMM_GPU through a Docker setup for isolation and reproducibility of the CUDA environment The NVIDIA-Docker runtime needs to be installed to expose the driver to the container
  • GitHub - pytorch FBGEMM: FB (Facebook) + GEMM (General Matrix-Matrix . . .
    FBGEMM (Facebook GEneral Matrix Multiplication) is a low-precision, high-performance matrix-matrix multiplications and convolution library for server-side inference
  • fbgemm-gpu · PyPI
    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
  • Files | Anaconda. org
    FBGEMM (Facebook GEneral Matrix Multiplication) is a low-precision, high-performance matrix-matrix multiplications and convolution library for server-side inference
  • Releases · pytorch FBGEMM - GitHub
    It is recommended to prepare an isolated environment for installing and running FBGEMM_GPU, such as Conda and or Docker FBGEMM_GPU can be fetched directly from PyPI: # FBGEMM_GPU CPU variant Alternatively, it can be fetched from PyTorch PIP: # FBGEMM_GPU CPU variant [Improvement] Remove triton ops dependency from fbgemm (#3329)
  • Build Instructions — FBGEMM 1. 4. 0 documentation
    Setting the machine up for CUDA builds of FBGEMM_GPU can be done either through pre-built Docker images or through Conda installation on bare metal Note that neither a GPU nor the NVIDIA drivers need to be present for builds, since they are only used at runtime
  • Documentation — FBGEMM 1. 4. 0 documentation - PyTorch
    Follow the instructions for setting up the Conda environment at Set Up an Isolated Build Environment A build pass of FBGEMM_GPU is required for the documentation to be built correctly Follow the instructions in Install the Build Tools, followed by CPU-Only Build, to build FBGEMM_GPU (CPU variant) # !! Run inside the Conda environment !!
  • Build Instructions — FBGEMM 1. 4. 0 documentation
    Building FBGEMM GenAI for CUDA requires both NVML and cuDNN to be installed and made available to the build through environment variables The presence of a CUDA device, however, is not required for building the package


















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