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DTSTAMP:20211207T054812Z
LOCATION:220-221
DTSTART;TZID=America/Chicago:20211118T140000
DTEND;TZID=America/Chicago:20211118T143000
UID:submissions.supercomputing.org_SC21_sess164_pap410@linklings.com
SUMMARY:PAGANI: A Parallel Adaptive GPU Algorithm for Numerical Integratio
 n
DESCRIPTION:Paper\n\nPAGANI: A Parallel Adaptive GPU Algorithm for Numeric
 al Integration\n\nSakiotis, Arumugam, Paterno, Ranjan, Terzic...\n\nWe pre
 sent a new adaptive parallel algorithm for the challenging problem of mult
 i-dimensional numerical integration on massively parallel architectures. A
 daptive algorithms have demonstrated the best performance, but efficient m
 any-core utilization is difficult to achieve because the adaptive workload
  can vary greatly across the integration space and is impossible to predic
 t a priori. Existing parallel algorithms utilize sequential computations o
 n independent processors, which results in bottlenecks due to the need for
  data redistribution and processor synchronization. Our algorithm employs 
 a high throughput approach in which all existing sub-regions are processed
  and sub-divided in parallel. Repeated sub-region classification and filte
 ring improves upon a brute-force approach and allows the algorithm to make
  efficient use of computation and memory resources. A CUDA implementation 
 shows orders of magnitude speedup over the fastest open source CPU method 
 and extends the achievable accuracy for difficult integrands. Our algorith
 m typically outperforms other existing deterministic parallel methods.\n\n
 Tag: Reproducibility Badge, Algorithms, Numerical Algorithms\n\nRegistrati
 on Category: Tech Program Reg Pass\n\nReproducibility Badges: Artifact Ava
 ilable, Artifact Functional, Results Reproduced
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