Efficiently Exploiting Irregular Parallelism Using Keys at Scale

doi:10.1007/978-3-032-02436-7_6

Efficiently Exploiting Irregular Parallelism Using Keys at Scale

2026-01-01

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Wang, Yuqing *

R

Rajasukumar, Andronicus

Diaz, Jose M. Monsalve

DOI：10.1007/978-3-032-02436-7_6

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Motivated by the challenges of programming irregular applications for machines with million-fold parallelism, we present a key-based programming model, called key-value map-shuffle-reduce (KVMSR), that enables programmers to optimize fine-grained parallel programs. KVMSR expresses parallelism on a global address space and features modular interfaces to flexibly bind computation to available compute resources. We define the KVMSR model and illustrate it with three programs, convolution filter, PageRank and BFS, to show its ability to separate computation expression from binding to computation location for high performance. On a 8,192-way parallel compute system, KVMSR modular computation location control achieves up to 2,317x performance with static approaches and an increase of 549x to 2,715x speedup with dynamic approaches for computation location binding.

Keywords:

graph computing

parallel computing

fine-grained parallelism

scalable computing

high-performance computing

map-reduce

Efficiently Exploiting Irregular Parallelism Using Keys at Scale

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