|Date||September 15, 2016|
University of California, Riverside
|Title||Parallel Graph Processing on GPUs, Clusters, and Multicores|
|Abstract||The importance of iterative graph algorithms has grown due to their widespread use in graph mining and analytics. Although computations on graphs with millions of nodes and edges contain vast amounts of data level parallelism, exploiting this parallelism is challenging due to the highly irregular nature of real-world graphs. In this talk I will present our recent results that greatly improve the SIMD-efficiency, communication efficiency, and I/O efficiency of graph processing on GPUs, a cluster, and a single multicore machine. In comparison to prior techniques, our Warp Segmentation technique achieves 1.3x-2.8x performance improvement on a single GPU, our Vertex Refinement technique achieves 2.7x performance improvement on a multi-GPU system, our Relaxed Consistency protocol achieves 2.3x performance improvement on a 16-node cluster, and our Dynamic Shards I/O optimization achieves up to 2.8x performance improvement on a single multicore machine.|
|Bio||Rajiv is a Professor of Computer Science at the University of California, Riverside. His research interests include Compilers, Architectures, and Runtimes for Parallel Systems. He has supervised PhD dissertations of 28 students including two winners of ACM SIGPLAN Outstanding Doctoral Dissertation Award. Papers coauthored by Rajiv with his students have been selected for: inclusion in 20 Years of PLDI (1979-1999), a best paper award in PACT 2010, and a distinguished paper award in ICSE 2003. Rajiv is a Fellow of the ACM, IEEE, and AAAS. He received the National Science Foundation's Presidential Young Investigator Award and UCR Doctoral Dissertation Advisor/Mentor Award. He has chaired several major conferences including FCRC, PLDI, HPCA, ASPLOS, CGO, CC, HiPEAC, and LCTES. He serves on the Editorial Boards of ACM Transactions on Architecture and Code Optimization and Parallel Computing journal. Rajiv served as a member of a technical advisory group on networking and information technology created by the PCAST.|
These seminars supported by the Ming Hsieh Institute.