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    <title>F# Tensor (multidimensional array) library with SIMD and GPU acceleration</title>
    <summary>Provides n-dimensional arrays (tensors) in host memory or on CUDA GPUs. Support many operations from NumPy.</summary>
    <description>
      Tensor (n-dimensional array) library for F#

      Core features:
        - n-dimensional arrays (tensors) in host memory or on CUDA GPUs 
        - element-wise operations (addition, multiplication, absolute value, etc.)
        - basic linear algebra operations (dot product, SVD decomposition, matrix inverse, etc.)
        - reduction operations (sum, product, average, maximum, arg max, etc.)
        - logic operations (comparision, and, or, etc.)
        - views, slicing, reshaping, broadcasting (similar to NumPy) 
        - scatter and gather by indices
        - standard functional operations (map, fold, etc.)

      Data exchange:
        - read/write support for HDF5 (.h5)
        - interop with standard F# types (Seq, List, Array, Array2D, Array3D, etc.)

      Performance:
        - host: SIMD and Intel MKL accelerated operations 
        - CUDA GPU: all operations performed locally on GPU and cuBLAS used for matrix operations

      Requirements: 
        - Linux or Windows on x64 only
        - for GPU support: CUDA 8.0 libraries installed and in PATH (Windows) or LD_LIBRARY_PATH (Linux)

      Additional algorithms are provided in the Tensor.Algorithms package.
    </description>
    <PackageTags>Tensor ndarray array MKL SIMD BLAS CUDA CUBLAS HDF5</PackageTags>
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