Evaluating the potential of multithreaded platforms for irregular scientific computations
Proceedings of the 4th international conference on Computing frontiers
Fast and scalable list ranking on the GPU
Proceedings of the 23rd international conference on Supercomputing
Locality behavior of parallel and sequential algorithms for irregular graph problems
PDCS '07 Proceedings of the 19th IASTED International Conference on Parallel and Distributed Computing and Systems
Petascale computing for large-scale graph problems
PPAM'07 Proceedings of the 7th international conference on Parallel processing and applied mathematics
Fast PGAS Implementation of Distributed Graph Algorithms
Proceedings of the 2010 ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis
Scalable Graph Exploration on Multicore Processors
Proceedings of the 2010 ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis
System implications of memory reliability in exascale computing
Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis
Better speedups using simpler parallel programming for graph connectivity and biconnectivity
Proceedings of the 2012 International Workshop on Programming Models and Applications for Multicores and Manycores
Proceedings of the 17th ACM SIGPLAN symposium on Principles and Practice of Parallel Programming
Introducing ScaleGraph: an X10 library for billion scale graph analytics
Proceedings of the 2012 ACM SIGPLAN X10 Workshop
Highly scalable graph search for the Graph500 benchmark
Proceedings of the 21st international symposium on High-Performance Parallel and Distributed Computing
Breaking the speed and scalability barriers for graph exploration on distributed-memory machines
SC '12 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis
Large-scale energy-efficient graph traversal: a path to efficient data-intensive supercomputing
SC '12 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis
Massive data analytics: the graph 500 on IBM Blue Gene/Q
IBM Journal of Research and Development
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Combinatorial problems such as those from graph theory pose serious challenges for parallel machines due to non-contiguous, concurrent accesses to global data structures with low degrees of locality. The hierarchical memory systems of symmetric multiprocessor (SMP) clusters optimize for local, contiguous memory accesses, and so are inefficient platforms for such algorithms. Few parallel graph algorithms outperform their best sequential implementation on SMP clusters due to long memory latencies and high synchronization costs. In this paper, we consider the performance and scalability of two graph algorithms, list ranking and connected components, on two classes of shared-memory computers: symmetric multiprocessors such as the Sun Enterprise servers and multithreaded architectures (MTA) such as the Cray MTA-2. While previous studies have shown that parallel graph algorithms can speedup on SMPs, the systemsý reliance on cache microprocessors limits performance. The MTAýs latency tolerant processors and hardware support for fine-grain synchronization makes performance a function of parallelism. Since parallel graph algorithms have an abundance of parallelism, they perform and scale significantly better on the MTA. We describe and give a performance model for each architecture. We analyze the performance of the two algorithms and discuss how the features of each architecture affects algorithm development, ease of programming, performance, and scalability.