Hierarchically tiled arrays for parallelism and locality

Authors:
Jia Guo;Ganesh Bikshandi;Daniel Hoeflinger;Gheorghe Almasi;Basilio Fraguela;María Jesús Garzará;David Padua;Christoph von Praun
Affiliations:
University of Illinois at Urbana-Champaign;University of Illinois at Urbana-Champaign;University of Illinois at Urbana-Champaign;IBM T.J. Watson Research Center, Yorktown Heights;Universidade da Coruña, Spain;University of Illinois at Urbana-Champaign;University of Illinois at Urbana-Champaign;IBM T.J. Watson Research Center, Yorktown Heights
Venue:
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
Year:
2006

Citing 14
Cited 3

A data locality optimizing algorithm

PLDI '91 Proceedings of the ACM SIGPLAN 1991 conference on Programming language design and implementation
Compiling Fortran D for MIMD distributed-memory machines

Communications of the ACM
An overview of High Performance Fortran

ACM SIGPLAN Fortran Forum
PVM: Parallel virtual machine: a users' guide and tutorial for networked parallel computing

PVM: Parallel virtual machine: a users' guide and tutorial for networked parallel computing
The art of computer programming, volume 2 (3rd ed.): seminumerical algorithms

The art of computer programming, volume 2 (3rd ed.): seminumerical algorithms
Co-array Fortran for parallel programming

ACM SIGPLAN Fortran Forum
Techniques for the translation of MATLAB programs into Fortran 90

ACM Transactions on Programming Languages and Systems (TOPLAS)
Using MPI (2nd ed.): portable parallel programming with the message-passing interface

Using MPI (2nd ed.): portable parallel programming with the message-passing interface
MaJIC: compiling MATLAB for speed and responsiveness

PLDI '02 Proceedings of the ACM SIGPLAN 2002 Conference on Programming language design and implementation
The Case for High-Level Parallel Programming in ZPL

IEEE Computational Science & Engineering
MultiMATLAB: MATLAB on Multiple Processors

MultiMATLAB: MATLAB on Multiple Processors
Parallelism exposure and exploitation in programs

Parallelism exposure and exploitation in programs
Distributed pC++ Basic Ideas for an Object Parallel Language

Scientific Programming
STAPL: an adaptive, generic parallel C++ library

LCPC'01 Proceedings of the 14th international conference on Languages and compilers for parallel computing

Towards a holistic approach to auto-parallelization: integrating profile-driven parallelism detection and machine-learning based mapping

Proceedings of the 2009 ACM SIGPLAN conference on Programming language design and implementation
Rigel: an architecture and scalable programming interface for a 1000-core accelerator

Proceedings of the 36th annual international symposium on Computer architecture
On-chip cache hierarchy-aware tile scheduling for multicore machines

CGO '11 Proceedings of the 9th Annual IEEE/ACM International Symposium on Code Generation and Optimization

Quantified Score

Hi-index	0.00

Visualization

Abstract

Parallel programming is facilitated by constructs which, unlike the widely used SPMD paradigm, provide programmers with a global view of the code and data structures. These constructs could be compiler directives containing information about data and task distribution, language extensions specifically designed for parallel computation, or classes that encapsulate parallelism. In this paper, we describe a class developed at Illinois and its MATLAB implementation. This class can be used to conveniently express both parallelism and locality. A C++ implementation is now underway. Its characteristics will be reported in a future paper. We have implemented most of the NAS benchmarks using our HTA MATLAB extensions and found during that HTAs enable the fast prototyping of parallel algorithms and produce programs that are easy to understand and maintain.