2016/10/05 by Karl Fürlinger, Tobias Fuchs, Fürlinger, Karl +4 · 1 voice
Computer Science · #Advanced Data Storage Technologies #Distributed #Distributed and Parallel Computing Systems #FOS: Computer and information sciences #Parallel #Parallel Computing and Optimization Techniques #Peer-to-Peer Network Technologies #and Cluster Computing (cs.DC) #cs.DC
paper · pdf · doi:10.48550/arxiv.1610.01482
openalex publication_date 2016/10/05 · arxiv published 2016/10/05 · arxiv updated 2016/10/05 · openalex created_date 2022/10/02 · openalex updated_date 2026/07/28
We present DASH, a C++ template library that offers distributed data\nstructures and parallel algorithms and implements a compiler-free PGAS\n(partitioned global address space) approach. DASH offers many productivity and\nperformance features such as global-view data structures, efficient support for\nthe owner-computes model, flexible multidimensional data distribution schemes\nand inter-operability with STL (standard template library) algorithms. DASH\nalso features a flexible representation of the parallel target machine and\nallows the exploitation of several hierarchically organized levels of locality\nthrough a concept of Teams. We evaluate DASH on a number of benchmark\napplications and we port a scientific proxy application using the MPI two-sided\nmodel to DASH. We find that DASH offers excellent productivity and performance\nand demonstrate scalability up to 9800 cores.\n