Adaptive Task Size Control on High Level Programming for GPU/CPU Work Sharing

International audienceOn the work sharing among GPUs and CPU cores on GPU equipped clusters, it is a critical issue to keep load balance among these heterogeneous computing resources. We have been developing a runtime system for this problem on PGAS language named XcalableMP- dev/StarPU [1]. Through the development, we found the necessity of adaptive load balancing for GPU/CPU work sharing to achieve the best performance for various application codes. In this paper, we enhance our language system XcalableMP-dev/StarPU to add a new feature which can control the task size to be assigned to these heterogeneous resources dynamically during application execution. As a result of performance evaluation on several benchmarks, we confirmed the proposed feature correctly works and the performance with heterogeneous work sharing provides up to about 40% higher performance than GPU-only utilization even for relatively small size of problems

XcalableMP PGAS Programming Language

XcalableMP is a directive-based parallel programming language based on Fortran and C, supporting a Partitioned Global Address Space (PGAS) model for distributed memory parallel systems. This open access book presents XcalableMP language from its programming model and basic concept to the experience and performance of applications described in XcalableMP.　 XcalableMP was taken as a parallel programming language project in the FLAGSHIP 2020 project, which was to develop the Japanese flagship supercomputer, Fugaku, for improving the productivity of parallel programing. XcalableMP is now available on Fugaku and its performance is enhanced by the Fugaku interconnect, Tofu-D. The global-view programming model of XcalableMP, inherited from High-Performance Fortran (HPF), provides an easy and useful solution to parallelize data-parallel programs with directives for distributed global array and work distribution and shadow communication. The local-view programming adopts coarray notation from Coarray Fortran (CAF) to describe explicit communication in a PGAS model. The language specification was designed and proposed by the XcalableMP Specification Working Group organized in the PC Consortium, Japan. The Omni XcalableMP compiler is a production-level reference implementation of XcalableMP compiler for C and Fortran 2008, developed by RIKEN CCS and the University of Tsukuba. The performance of the XcalableMP program was used in the Fugaku as well as the K computer. A performance study showed that XcalableMP enables a scalable performance comparable to the message passing interface (MPI) version with a clean and easy-to-understand programming style requiring little effort

筑波大学計算科学研究センター 平成25年度 年次報告書

1 平成25 年度重点施策および改善目標の達成状況 ...... 22 自己評価と課題 ...... 83 各研究部門の報告 ...... 10I. 素粒子物理研究部門 ...... 10II. 宇宙・原子核物理研究部門 ...... 32II-1. 宇宙物理理論グループ ...... 32II-2. 原子核分野 ...... 56III. 量子物性研究部門 ...... 69IV. 生命科学研究部門 ...... 83IV-1. 生命機能情報分野 ...... 83IV-2. 分子進化分野 ...... 93V. 地球環境研究部門 ....... 104VI. 高性能計算システム研究部門 ...... 118VII. 計算情報学研究部門 ...... 148VII-1. データ基盤分野 ...... 148VII-2. 計算メディア分野 ...... 16