PCJ - Java library for high performance computing in PGAS model

Abstract

This paper presents the application of the PCJ library for the parallelization of the selected HPC applications implemented in Java language. The library is motivated by partitioned global address space (PGAS) model represented by Co-Array Fortran, Unified Parallel C, X10 or Titanium.In the PCJ, each task has its own local memory and stores and access variables locally. Variables can be shared between tasks and can be accessed, read and modified by other tasks. The library provides methods to perform basic operations like synchronization of tasks, get and put values in asynchronous onesided way. Additionally the library offers methods for creating groups of tasks, broadcasting and monitoring variables. The PCJ has ability to work on the multinode multicore systems hiding details of inter-and intranode communication. The PCJ library fully complies with Java standards therefore the programmer does not have to use additional libraries, which are not part of the standard Java distribution.In this paper the PCJ library has been used to run example HPC applications on the multicore nodes. In particular we present performance results for parallel raytracing, matrix multiplication and map-reduce calculations. The detailed information on performance of the reduction operation is also presented.The results show good performance and scalability compared to native implementations of the same algorithms. In particular, MPI C++ and Java 8 parallel streams have been used as a reference. It is noteworthy that the PCJ library due to its performance and ability to create simple code has great promise to be successful for parallelization of the HPC applications.

A multithreaded CUDA and OpenMP based power‐aware programming framework for multi‐node GPU systems

“…Several compliant languages and libraries have been discussed in Reference 16 including: original PGAS languages—CAF, Titanium, UPC; HPCS PGAS languages—Chapel, X10, Fortress; Retrospective PGAS languages—HPF, ZPL and GA as well as XCalableMP (XMP)—PGAS extension for C and Fortran. Notable recent examples include using PCJ for HPC systems, 17 big data processing, 18 clouds 19 as well as Shoal for clusters of processors and FPGAs 20 . HPX 21 is a C++ library developed for concurrency and parallelism that supports parallel, concurrent and distributed functions for general purpose programming, in particular active global address space (AGAS) that allows moving objects between nodes without changing addresses.…”

Mixed-Language Programming with XcalableMP

“…Because the use of PGAS languages is familiar in one-sided communication, applications in PGAS languages can sometimes exhibit higher performance than those using MPI library by directly using a communication layer close to hardware [5,6]. Examples of PGAS languages include XcalableMP (XMP) [5,7,8]; XcalableACC [9][10][11]; Coarray Fortran [12], PCJ [13], Unified Parallel C, 1 UPC++ [14], HabaneroUPC++ [15], X10 [16], Chapel [17], and DASH [18].…”