PAGANI: A Parallel Adaptive GPU Algorithm for Numerical Integration

We present a new adaptive parallel algorithm for the challenging problem of multi-dimensional numerical integration on massively parallel architectures. Adaptive algorithms have demonstrated the best performance, but efficient many-core utilization is difficult to achieve because the adaptive work-l...

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Veröffentlicht in:SC21: International Conference for High Performance Computing, Networking, Storage and Analysis S. 1 - 13
Hauptverfasser: Sakiotis, Ioannis, Arumugam, Kamesh, Paterno, Marc, Ranjan, Desh, Terzic, Balssa, Zubair, Mohammad
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: ACM 14.11.2021
Schlagworte:
adaptive
Classification algorithms
deterministic
Graphics processing units
integration
Memory management
multi-dimensional
Parallel architectures
Prediction algorithms
Programming
Prototypes
ISSN:2167-4337
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Beschreibung
Zusammenfassung:We present a new adaptive parallel algorithm for the challenging problem of multi-dimensional numerical integration on massively parallel architectures. Adaptive algorithms have demonstrated the best performance, but efficient many-core utilization is difficult to achieve because the adaptive work-load can vary greatly across the integration space and is impossible to predict a priori. Existing parallel algorithms utilize sequential computations on 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 filtering 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 algorithm typically outperforms other existing deterministic parallel methods.
ISSN:2167-4337
DOI:10.1145/3458817.3476198