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UID:submissions.supercomputing.org_SC20_sess162_pap215@linklings.com
SUMMARY:Task Bench: A Parameterized Benchmark for Evaluating Parallel Runt
 ime Performance
DESCRIPTION:Paper\n\nTask Bench: A Parameterized Benchmark for Evaluating 
 Parallel Runtime Performance\n\nSlaughter, Wu, Fu, Brandenburg, Garcia...\
 n\nWe present Task Bench, a parameterized benchmark designed to explore th
 e performance of distributed programming systems under a variety of applic
 ation scenarios. Task Bench dramatically lowers the barrier to benchmarkin
 g and comparing multiple programming systems by making the implementation 
 for a given system orthogonal to the benchmarks themselves: every benchmar
 k constructed with Task Bench runs on every Task Bench implementation. Fur
 thermore, Task Bench’s parameterization enables a wide variety of benchmar
 k scenarios that distill the key characteristics of larger applications.\n
 \nTo assess the effectiveness and overheads of the tested systems, we intr
 oduce a novel metric; minimum effective task granularity (METG). We conduc
 t a comprehensive study with 15 programming systems on up to 256 Haswell n
 odes of the Cori supercomputer. Running at scale, 100μs-long tasks ar
 e the finest granularity that any system runs efficiently with current tec
 hnologies. We also study each system’s scalability and ability to hide com
 munication, and mitigate load imbalance.\n\nTag: Machine Learning, Deep Le
 arning and Artificial Intelligence, Requirements, Performance, and Benchma
 rks, Reliability and Resiliency\n\nRegistration Category: Tech Program Reg
  Pass
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