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Showing 3 open source projects for "arm"

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    ERP Software To Simplify Your Manufacturing

    From quote to cash and with AI in mind, our ERP software will become the most valuable asset at your company.

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  • 1
    XNNPACK

    XNNPACK

    High-efficiency floating-point neural network inference operators

    XNNPACK is a highly optimized, low-level neural network inference library developed by Google for accelerating deep learning workloads across a variety of hardware architectures, including ARM, x86, WebAssembly, and RISC-V. Rather than serving as a standalone ML framework, XNNPACK provides high-performance computational primitives—such as convolutions, pooling, activation functions, and arithmetic operations—that are integrated into higher-level frameworks like TensorFlow Lite, PyTorch Mobile, ONNX Runtime, TensorFlow.js, and MediaPipe. ...
    Downloads: 3 This Week
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  • 2
    libjpeg-turbo

    libjpeg-turbo

    SIMD-accelerated libjpeg-compatible JPEG codec library

    libjpeg-turbo is a JPEG image codec that uses SIMD instructions (MMX, SSE2, NEON, AltiVec) to accelerate baseline JPEG compression and decompression on x86, x86-64, ARM, and PowerPC systems. On such systems, libjpeg-turbo is generally 2-6x as fast as libjpeg, all else being equal. On other types of systems, libjpeg-turbo can still outperform libjpeg by a significant amount, by virtue of its highly-optimized Huffman coding routines. In many cases, the performance of libjpeg-turbo rivals that of proprietary high-speed JPEG codecs. ...
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    Downloads: 46,434 This Week
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  • 3
    FastFlow: programming multi-core

    FastFlow: programming multi-core

    Pattern-based multi/many-core parallel programming framework

    ...Thanks to its very efficient CAS-free communication/synchronization support (e.g. few clock cycles core-to-core latency), FastFlow effectively supports the exploitation of fine grain parallelism, e.g. parallel codes managing very high frequency streams on commodity multi-core. FastFlow works on x86, x86_64, PPC, ARM, and Linux, Mac and Win XP/7. From Jan 1, 2018 code development migrated on GitHub at https://github.com/fastflow/fastflow
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    Downloads: 0 This Week
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