Uintah+Hedgehog: Combining Parallelism Models for End-to-End Large-Scale Simulation Performance
Event Type
Workshop
Online Only
Algorithms
Architectures
Extreme Scale Comptuing
Heterogeneous Systems
Memory Systems
Parallel Programming Languages and Models
Resource Management and Scheduling
W
TimeSunday, 14 November 20213:30pm - 4pm CST
LocationOnline
DescriptionThe complexity of heterogeneous nodes near and at exascale has increased the need for “heroic” programming efforts. To accommodate this complexity, significant investment is required for codes not yet optimizing for low-level architecture features (e.g., wide vector units) and/or running at large-scale. This paper describes ongoing efforts to combine two codes, Hedgehog and Uintah, lying at both extremes to ease programming efforts. The end goals of this effort are (1) to combine the two codes to make an asynchronous many-task runtime system specializing in both node-level and large-scale performance and (2) to further improve the accessibility of both with portable abstractions. A prototype adopting Hedgehog in Uintah and a prototype extending Hedgehog to support MPI+X hybrid parallelism are discussed. Results achieving ∼60% of NVIDIA V100 GPU peak performance for a distributed DGEMM problem are shown for a naive MPI+Hedgehog implementation before any attempt to optimize for performance.
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