Design Issues in Parallel Array Languages for Shared Memory

Authors:
James Brodman;Basilio B. Fraguela;María J. Garzarán;David Padua
Affiliations:
Dept. of Computer Science, University of Illinois at Urbana-Champaign, Urbana, USA IL 61801;Dept. de Electrónica y Sistemas, Universidade da Coruña, A Coruña, Spain 15071;Dept. of Computer Science, University of Illinois at Urbana-Champaign, Urbana, USA IL 61801;Dept. of Computer Science, University of Illinois at Urbana-Champaign, Urbana, USA IL 61801
Venue:
SAMOS '08 Proceedings of the 8th international workshop on Embedded Computer Systems: Architectures, Modeling, and Simulation
Year:
2008

Citing 10
Cited 0

A data locality optimizing algorithm

PLDI '91 Proceedings of the ACM SIGPLAN 1991 conference on Programming language design and implementation
Programming with POSIX threads

Programming with POSIX threads
Co-array Fortran for parallel programming

ACM SIGPLAN Fortran Forum
Parallel programming in OpenMP

Parallel programming in OpenMP
Organizing matrices and matrix operations for paged memory systems

Communications of the ACM
The Case for High-Level Parallel Programming in ZPL

IEEE Computational Science & Engineering
Programming for parallelism and locality with hierarchically tiled arrays

Proceedings of the eleventh ACM SIGPLAN symposium on Principles and practice of parallel programming
The ILLIAC IV Computer

IEEE Transactions on Computers
Programming with tiles

Proceedings of the 13th ACM SIGPLAN Symposium on Principles and practice of parallel programming
Intel threading building blocks

Intel threading building blocks

Quantified Score

Hi-index	0.00

Visualization

Abstract

The Hierarchically Tiled Array (HTA) is a data type that facilitates the definition and manipulation of arrays partitioned into tiles. The data type allows to exploit those tiles to attain both locality and parallelism. Parallel programs written with HTAs are based in data parallelism, and provide the programmer with a single-threaded view of the execution. In our experience, HTAs help to develop parallel codes in a much more productive way than other parallel programming approaches. While we have worked extensively with HTAs in distributed memory environments, only recently have we began to consider their adaption to shared memory environments such as those found in multicore systems. In this paper we review the design issues, opportunities and challenges that this migration raises.