Automatic GPU Data Compression and Address Swizzling for CPUs via Modified Virtual Address Translation

L. Seiler, Daqi Lin, Cem Yuksel
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引用次数: 1

Abstract

We describe how to modify hardware page translation to enable CPU software access to compressed and swizzled GPU data arrays as if they were decompressed and stored in row-major order. In a shared memory system, this allows CPU to directly access the GPU data without copying the data or losing the performance and bandwidth benefits of using compression and swizzling on the GPU. Our method is flexible enough to support a wide variety of existing and future swizzling and compression schemes, including block-based lossless compression that requires per-block meta-data. Providing automatic compression can improve performance, even without considering the cost of copying data. In our experiments, we observed up to 33% reduction in CPU/memory energy use and up to 35% reduction in CPU computation time.
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自动GPU数据压缩和地址转换的cpu通过修改虚拟地址转换
我们描述了如何修改硬件页面转换,以使CPU软件能够访问压缩和混合的GPU数据数组,就好像它们被解压缩并按行主顺序存储一样。在共享内存系统中,这允许CPU直接访问GPU数据,而无需复制数据或失去在GPU上使用压缩和搅拌的性能和带宽优势。我们的方法足够灵活,可以支持各种现有和未来的混合和压缩方案,包括需要每个块元数据的基于块的无损压缩。提供自动压缩可以提高性能,即使不考虑复制数据的成本。在我们的实验中,我们观察到CPU/内存能耗减少了33%,CPU计算时间减少了35%。
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