Designing Efficient Many-Core Parallel Algorithms for All-Pairs Shortest-Paths Using CUDA

Finding the all-pairs shortest-paths on a large graph is a fundamental problem in many practical applications such as bioinformatics, internet node traffic and network routing. In this paper, we present the designs of two efficient parallel algorithms for many-core GPUs using CUDA. Our algorithms ex...

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Bibliographic Details
Published in:2010 Seventh International Conference on Information Technology: New Generations pp. 7 - 12
Main Author: Tran, Quoc-Nam
Format: Conference Proceeding
Language:English
Published: IEEE 01.04.2010
Subjects:
Algorithm design and analysis
Concurrent computing
Graph Algorithms
Multi-core
Multi-threaded Algorithms
Multicore processing
Parallel algorithms
Parallel processing
Read-write memory
Routing
ISBN:9781424462704, 1424462703
Online Access:Get full text
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Summary:Finding the all-pairs shortest-paths on a large graph is a fundamental problem in many practical applications such as bioinformatics, internet node traffic and network routing. In this paper, we present the designs of two efficient parallel algorithms for many-core GPUs using CUDA. Our algorithms expose substantial fine-grained parallelism while maintaining minimal global communication. By using the global scope of the GPU's global memory, coalescing the global memory reads and writes, and avoiding on-chip shared memory bank conflicts, we are able to achieve a large performance benefit with a speed-up of 2,500x on a desktop computer in comparison with a single core program. Our algorithms are scalable, which can handle graphs with size larger than the memory available on the GPUs and when multiple GPUs are added into the system.
ISBN:9781424462704
1424462703
DOI:10.1109/ITNG.2010.230