Advances in Domain Mapping of Massively Parallel Scientific Computations
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
One of the most important concerns in parallel computing is the proper distribution of workload across processors. For most scientific applications on massively parallel machines, the best approach to this distribution is to employ data parallelism; that is, to break the datastructures supporting a computation into pieces and then to assign those pieces to different processors. Collectively, these partitioning and assignment tasks comprise the domain mapping problem.
- Research Organization:
- Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
- Sponsoring Organization:
- USDOE National Nuclear Security Administration (NNSA)
- DOE Contract Number:
- AC04-94AL85000
- OSTI ID:
- 1331498
- Report Number(s):
- SAND2015--8747R; 615285
- Country of Publication:
- United States
- Language:
- English
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