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Awesome GitHub RepositoriesGPU Framework Data Exchanges
Zero-copy sharing of GPU array data between different deep learning frameworks.
Distinct from Shared Memory Data Exchange: Distinct from Shared Memory Data Exchange: focuses on GPU array exchange between ML frameworks, not inter-process shared memory.
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Awesome GPU Framework Data Exchanges GitHub Repositories
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- nvidia/warp
NVIDIA/warp
6,233在 GitHub 上查看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
Exchanges GPU array data with PyTorch and JAX through the CUDA array interface without copying.
Pythoncudadifferentiable-programminggpu
