Heterogeneous combinatorial candidate generation

Authors:
Fahad Khalid;Zoran Nikoloski;Peter Tröger;Andreas Polze
Affiliations:
Hasso Plattner Institute for Software Systems Engineering, Germany;Max Planck Insitute of Molecular Plant Physiology, Germany;Hasso Plattner Institute for Software Systems Engineering, Germany;Hasso Plattner Institute for Software Systems Engineering, Germany
Venue:
Euro-Par'13 Proceedings of the 19th international conference on Parallel Processing
Year:
2013

Citing 11
Cited 0

Parallel Out-of-Core Algorithm for Genome-Scale Enumeration of Metabolic Systemic Pathways

IPDPS '02 Proceedings of the 16th International Parallel and Distributed Processing Symposium
Double Description Method Revisited

Selected papers from the 8th Franco-Japanese and 4th Franco-Chinese Conference on Combinatorics and Computer Science
Sourcebook of parallel computing

Sourcebook of parallel computing
Improving the computational intensity of unstructured mesh applications

Proceedings of the 19th annual international conference on Supercomputing
Large-scale computation of elementary flux modes with bit pattern trees

Bioinformatics
Solving path problems on the GPU

Parallel Computing
Parallel extreme ray and pathway computation

PPAM'09 Proceedings of the 8th international conference on Parallel processing and applied mathematics: Part II
Divide-and-Conquer Approach to the Parallel Computation of Elementary Flux Modes in Metabolic Networks

IPDPSW '11 Proceedings of the 2011 IEEE International Symposium on Parallel and Distributed Processing Workshops and PhD Forum
Accelerating the computation of elementary modes using pattern trees

WABI'06 Proceedings of the 6th international conference on Algorithms in Bioinformatics
Applications of Heterogeneous Computing in Computational and Simulation Science

UCC '11 Proceedings of the 2011 Fourth IEEE International Conference on Utility and Cloud Computing
LU Factorization with Partial Pivoting for a Multicore System with Accelerators

IEEE Transactions on Parallel and Distributed Systems

Quantified Score

Hi-index	0.00

Visualization

Abstract

Elementary Flux Modes (EFMs) can be used to characterize functional cellular networks and have gained importance in systems biology. Enumeration of EFMs is a compute-intensive problem due to the combinatorial explosion in candidate generation. While there exist parallel implementations for shared-memory SMP and distributed memory architectures, tools supporting heterogeneous platforms have not yet been developed. Here we propose and evaluate a heterogeneous implementation of combinatorial candidate generation that employs GPUs as accelerators. It uses a 3-stage pipeline based method to manage arithmetic intensity. Our implementation results in a 6x speedup over the serial implementation, and a 1.8x speedup over a multithreaded implementation for CPU-only SMP architectures.