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Back to ddemidov/vexcl

Open-source alternatives to Vexcl

30 open-source projects similar to ddemidov/vexcl, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best Vexcl alternative.

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    ARCHIVED The C++ Standard Library for your entire system. See https://github.com/NVIDIA/cccl

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    Thrust is a heterogeneous computing library and C++ template library that provides a collection of high-level templates for executing data-parallel operations. It functions as a parallel algorithms library designed to work across different hardware backends, including multicore CPUs and NVIDIA GPU hardware. The framework utilizes a header-only implementation and a generic-programming policy interface to abstract the differences between CPU and GPU memory and execution models. It employs an iterator-based data abstraction to provide a uniform interface for accessing elements across host RAM an

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    NVIDIA/TensorRT

    13,076在 GitHub 上查看↗

    TensorRT is a deep learning inference engine and software development kit designed to optimize and deploy neural networks for high-performance execution on NVIDIA GPUs. It functions as a GPU acceleration framework that reduces latency and increases throughput for trained models during production deployment. The toolkit imports models from the Open Neural Network Exchange format and transforms them into optimized engines. It utilizes graph-based model optimization, layer-fusion kernel generation, and precision-based quantization to convert floating point weights into lower precision formats.

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    CuPy is a CUDA array computing library that implements a NumPy-compatible interface for executing array operations and numerical computing on NVIDIA GPUs. It serves as a GPU-accelerated numerical library and a CUDA-based SciPy implementation, offloading heavy calculations to graphics hardware to increase processing speed for scientific and engineering workloads. The library enables multi-framework tensor exchange, allowing data buffers to be shared between different deep learning frameworks using standardized memory layouts to avoid memory copies. It also supports custom GPU kernel integratio

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    This project is a structured Rust programming curriculum and systems programming course designed to take learners from beginner to expert levels. It provides a comprehensive set of training materials focused on mastering the core syntax, idioms, and technical foundations of the Rust language. The project features a specialized language transition framework that maps concepts from C++, managed languages, and dynamic typing to Rust idioms. This allows developers from different ecosystems to translate architectural patterns and memory models into idiomatic Rust. The training covers a broad rang

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