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GAIA: An OS Page Cache for Heterogeneous Systems
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Tanya Brokhman , M.Sc. Thesis Seminar
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Wednesday, 27.2.2019, 11:30
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Electrical Eng. Building 861
We propose a principled approach to integrating GPU memory with an OS page cache. We design GAIA, a weakly-consistent page cache that spans CPU and GPU memories. GAIA enables the standard mmap system call to map files into the GPU address space, thereby enabling data-dependent GPU accesses to large files and efficient write-sharing between the CPU and GPUs. Under the hood, GAIA (1) integrates lazy release consistency among physical memories into the OS page cache while maintaining backward compatibility with CPU processes and unmodified GPU kernels; (2) improves CPU I/O performance by using data cached in GPU memory, and (3) optimizes readahead prefetcher to support accesses to caches in GPUs. We prototype GAIA in Linux and evaluate it on NVIDIA Pascal GPUs. We show up to 3 speedup in CPU file I/O and up to 8 in unmodified realistic workloads such as Gunrock GPU-accelerated graph processing, image collage, and microscopy i
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