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Awesome GitHub RepositoriesTile-Based Kernel Differentiators

Generates backward-mode gradient computations for tile-based GPU kernels, supporting in-place addition and subtraction.

Distinct from GPU Kernel Differentiators: Distinct from GPU Kernel Differentiators: focuses specifically on differentiating tile-based cooperative kernels, not general GPU kernel differentiation.

Explore 1 awesome GitHub repository matching part of an awesome list · Tile-Based Kernel Differentiators. Refine with filters or upvote what's useful.

Awesome Tile-Based Kernel Differentiators GitHub Repositories

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  • nvidia/warpAvatar NVIDIA

    NVIDIA/warp

    6,233Vezi pe GitHub↗

    Warp is a Python framework that JIT-compiles Python functions into CUDA kernels for GPU-accelerated parallel computation, with built-in automatic differentiation and multi-framework array interoperability. At its core, it provides a GPU kernel compilation system that enables writing and executing custom GPU kernels directly from Python, while supporting automatic gradient computation through those kernels for integration with machine learning pipelines. The framework also includes tile-based cooperative computing, where thread blocks partition into tiles for shared-memory and tensor-core opera

    Generates backward-mode gradient computations for tile-based kernels, supporting in-place addition and subtraction.

    Pythoncudadifferentiable-programminggpu
    Vezi pe GitHub↗6,233
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