Showing 2 open source projects for "automatic differentiation"

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    Taichi

    Taichi

    Productive, portable, and performant GPU programming in Python

    ...It uses JIT compilation (via LLVM and its runtime TiRT) to offload compute-heavy code to CPUs, GPUs, mobile devices, and embedded systems. With built-in support for sparse data structures (SNode), automatic differentiation, AOT deployment, and compatibility with CUDA, Vulkan, Metal, and OpenGL ES, it empowers disciplines like simulation, graphics, AI, and robotics
    Downloads: 0 This Week
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  • 2
    JAX

    JAX

    Composable transformations of Python+NumPy programs

    ...But JAX also lets you just-in-time compile your own Python functions into XLA-optimized kernels using a one-function API, jit. Compilation and automatic differentiation can be composed arbitrarily, so you can express sophisticated algorithms and get maximal performance without leaving Python.
    Downloads: 0 This Week
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