A high-productivity task-based programming model for clusters

Authors:
Enric Tejedor;Montse Farreras;David Grove;Rosa M. Badia;Gheorghe Almasi;Jesus Labarta
Affiliations:
Barcelona Supercomputing Center, BSC-CNS, Barcelona, Spain and Universitat Politècnica de Catalunya, UPC, Barcelona, Spain;Barcelona Supercomputing Center, BSC-CNS, Barcelona, Spain and Universitat Politècnica de Catalunya, UPC, Barcelona, Spain;IBM T.J. Watson Research Center, Yorktown Heights, NY 10598, USA;Barcelona Supercomputing Center, BSC-CNS, Barcelona, Spain and Artificial Intelligence Research Institute (IIIA), Spanish National Research Council (CSIC), Spain;IBM T.J. Watson Research Center, Yorktown Heights, NY 10598, USA;Barcelona Supercomputing Center, BSC-CNS, Barcelona, Spain and Universitat Politècnica de Catalunya, UPC, Barcelona, Spain
Venue:
Concurrency and Computation: Practice & Experience
Year:
2012

Citing 16
Cited 0

Active messages: a mechanism for integrated communication and computation

ISCA '92 Proceedings of the 19th annual international symposium on Computer architecture
Co-array Fortran for parallel programming

ACM SIGPLAN Fortran Forum
Java Native Interface: Programmer's Guide and Reference

Java Native Interface: Programmer's Guide and Reference
X10: an object-oriented approach to non-uniform cluster computing

OOPSLA '05 Proceedings of the 20th annual ACM SIGPLAN conference on Object-oriented programming, systems, languages, and applications
Parallel Programmability and the Chapel Language

International Journal of High Performance Computing Applications
CellSs: making it easier to program the cell broadband engine processor

IBM Journal of Research and Development
COMP Superscalar: Bringing GRID Superscalar and GCM Together

CCGRID '08 Proceedings of the 2008 Eighth IEEE International Symposium on Cluster Computing and the Grid
The deep computing messaging framework: generalized scalable message passing on the blue gene/P supercomputer

Proceedings of the 22nd annual international conference on Supercomputing
An Extension of the StarSs Programming Model for Platforms with Multiple GPUs

Euro-Par '09 Proceedings of the 15th International Euro-Par Conference on Parallel Processing
Parallel Scripting for Applications at the Petascale and Beyond

Computer
Effective communication and computation overlap with hybrid MPI/SMPSs

Proceedings of the 15th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming
A proposal to extend the OpenMP tasking model with dependent tasks

International Journal of Parallel Programming
Optimizing bandwidth limited problems using one-sided communication and overlap

IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
StarPU: a unified platform for task scheduling on heterogeneous multicore architectures

Concurrency and Computation: Practice & Experience - Euro-Par 2009
Asynchronous PGAS runtime for Myrinet networks

Proceedings of the Fourth Conference on Partitioned Global Address Space Programming Model
Exploiting Inherent Task-Based Parallelism in Object-Oriented Programming

GRID '11 Proceedings of the 2011 IEEE/ACM 12th International Conference on Grid Computing

Quantified Score

Hi-index	0.00

Visualization

Abstract

Programming for large-scale, multicore-based architectures requires adequate tools that offer ease of programming and do not hinder application performance. StarSs is a family of parallel programming models based on automatic function-level parallelism that targets productivity. StarSs deploys a data-flow model: it analyzes dependencies between tasks and manages their execution, exploiting their concurrency as much as possible. This paper introduces Cluster Superscalar (ClusterSs), a new StarSs member designed to execute on clusters of SMPs (Symmetric Multiprocessors). ClusterSs tasks are asynchronously created and assigned to the available resources with the support of the IBM APGAS runtime, which provides an efficient and portable communication layer based on one-sided communication. We present the design of ClusterSs on top of APGAS, as well as the programming model and execution runtime for Java applications. Finally, we evaluate the productivity of ClusterSs, both in terms of programmability and performance and compare it to that of the IBM X10 language. Copyright © 2012 John Wiley & Sons, Ltd.