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Scientific benchmarking of parallel computing systems: twelve ways to tell the masses when reporting performance results.

, and . SC, page 73:1-73:12. ACM, (2015)

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Abstract: Slack-Conscious Lightweight Loop Scheduling for Improving Scalability of Bulk-synchronous MPI Applications., , , , and . SC Companion, page 1392. IEEE Computer Society, (2012)Multistage switches are not crossbars: Effects of static routing in high-performance networks., , and . CLUSTER, page 116-125. IEEE Computer Society, (2008)Characterizing the Influence of System Noise on Large-Scale Applications by Simulation., , and . SC, page 1-11. IEEE, (2010)μ-cuDNN: Accelerating Deep Learning Frameworks with Micro-Batching., , , and . CoRR, (2018)Transformations of High-Level Synthesis Codes for High-Performance Computing., , and . CoRR, (2018)Communication-Avoiding Parallel Algorithms for Solving Triangular Systems of Linear Equations., , and . CoRR, (2016)Betweenness Centrality is more Parallelizable than Dense Matrix Multiplication., , , and . CoRR, (2016)Fault tolerance for remote memory access programming models., and . HPDC, page 37-48. ACM, (2014)DARE: High-Performance State Machine Replication on RDMA Networks., and . HPDC, page 107-118. ACM, (2015)Active pebbles: parallel programming for data-driven applications., , , and . ICS, page 235-244. ACM, (2011)