2018/11/13 by Victor Eijkhout, Eijkhout, Victor
Computer Science · #Cloud Computing and Resource Management #Distributed #Distributed and Parallel Computing Systems #FOS: Computer and information sciences #Parallel #Parallel Computing and Optimization Techniques #and Cluster Computing (cs.DC) #cs.DC
paper · pdf · doi:10.48550/arxiv.1811.05077
arxiv created 2018/11/13 · openalex publication_date 2018/11/13 · arxiv updated 2018/11/14 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The Integrative Model for Parallelism (IMP) derives a task graph from a higher level description of parallel algorithms. In this note we show how task graph transformations can be used to achieve latency tolerance in the program execution. We give a formal derivation of the graph transformation, and show through simulation how latency tolerant algorithms can be faster than the naive execution in a strong scaling scenario.