Blar i forfatter "Langguth, Johannes"

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    • Implementing and optimizing a Sparse Matrix-Vector Multiplication with UPC 

      Lagraviere, Jeremie Alexandre Emilien; Prugger, Martina; Einkemmer, Lukas; Langguth, Johannes; Ha, Hoai Phuong; Cai, Xing (Research report; Forskningsrapport, 2016)
      Programmability and performance-per-watt are the major challenges of the race to Exascale. In this study we focus on Partitioned Global Address Space (PGAS) languages, using UPC as a particular example. This category of parallel languages provides ease of programming as a strong advantage over the classic Message Passing Interface(MPI). PGAS has also advantages compared to classic shared memory ...

    • On the performance and energy efficiency of the PGAS programming model on multicore architectures 

      Lagraviere, Jeremie Alexandre Emilien; Langguth, Johannes; Sourouri, Mohammed; Ha, Hoai Phuong; Cai, Xing (Journal article; Tidsskriftartikkel; Peer reviewed, 2016-09-15)

    • Performance optimization and modeling of fine-grained irregular communication in UPC 

      Lagraviere, Jeremie Alexandre Emilien; Langguth, Johannes; Prugger, Martina; Einkemmer, Lukas; Ha, Hoai Phuong; Cai, Xing (Journal article; Tidsskriftartikkel; Peer reviewed, 2019-03-03)
      The Unified Parallel C (UPC) programming language offers parallelism via logically partitioned shared memory, which typically spans physically disjoint memory subsystems. One convenient feature of UPC is its ability to automatically execute between-thread data movement, such that the entire content of a shared data array appears to be freely accessible by all the threads. The programmer friendliness, ...