Title
A Power Characterization and Management of GPU Graph TraversalConference
Published at the Fourth Workshop on Architectures and Systems for Big Data (ASBD 2014), June, 2014 (acceptance rate: 6/13 ≈ 46%)Authors
Adam McLaughlin, Indrani Paul, Joseph L. Greathouse, Srilatha Manne, Sudhakar YalamanchiliAbstract
Graph analysis is a fundamental building block in numerous computing domains. Recent research has looked into harnessing GPUs to achieve necessary throughput goals. However, comparatively little attention has been paid to improving the power-constrained performance of these applications.
Through firmware changes on a state-of-the-art commodity GPU, we characterize the power consumption of Breadth-First Search (BFS) as a function of the structural properties of the graph. We choose to study this algorithm since graph traversals are used as a building block for many other graph analysis applications. Based on this characterization, we propose and evaluate a power management algorithm to maximize power cap efficiency, or the performance under a fixed power cap. Across a range of benchmark graphs, we demonstrate power cap efficiency improvements averaging 15.56% on a state-of-the-art GPU.