Large-Scale Graph Processing On Emerging Storage Devices
PROCEEDINGS OF THE 17TH USENIX CONFERENCE ON FILE AND STORAGE TECHNOLOGIES(2019)
摘要
Graph processing is becoming commonplace in many applications to analyze huge datasets. Much of the prior work in this area has assumed I/O devices with considerable latencies, especially for random accesses, using large amount of DRAM to trade-off additional computation for I/O accesses. However, emerging storage devices, including currently popular SSDs, provide fairly comparable sequential and random accesses, making these prior solutions inefficient. In this paper, we point out this inefficiency, and propose a new graph partitioning and processing framework to leverage these new device capabilities. We show experimentally on an actual platform that our proposal can give 2X better performance than a state-of-the-art solution.
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