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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.
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Awesome Tile-Based Kernel Differentiators GitHub Repositories
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- nvidia/warp
NVIDIA/warp
6,233GitHub पर देखेंWarp 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
