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Accelerating BP Neural Network-Based Image Compression by CPU and GPU Cooperation

机译:通过CPU和GPU协作加速基于BP神经网络的图像压缩

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Recently, GPU has evolved into a highly parallel, multithreading, many core processor with tremendous computational capability and very high memory bandwidth. At the same time, multi-core CPU evolution continued and today's CPUs have 4-8 cores which offer dramatically increased performance and power savings characteristics. We are aware of very few works that consider both devices cooperating to solve general computations. The article tries to bring forward a method of similar master/ worker GPU-CPU cooperative computing to improve efficiency of Back-Propagation neural network-based image compression application even further than using either device independently.
机译:最近,GPU已发展成为高度并行,多线程的许多核心处理器,具有强大的计算能力和非常高的内存带宽。同时,多核CPU的发展仍在继续,当今的CPU具有4-8个核,这些核提供了显着提高的性能和节能特性。我们知道很少有人考虑将两种设备配合使用以解决一般计算问题。本文试图提出一种类似的主/工人GPU-CPU协同计算的方法,以提高基于反向传播神经网络的图像压缩应用程序的效率,甚至比单独使用任一设备更进一步。

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