Faster optimal parallel prefix sums and list ranking
Information and Computation
A simple randomized parallel algorithm for list-ranking
Information Processing Letters
An introduction to parallel algorithms
An introduction to parallel algorithms
List ranking and list scan on the Cray C-90
SPAA '94 Proceedings of the sixth annual ACM symposium on Parallel algorithms and architectures
HiPC '02 Proceedings of the 9th International Conference on High Performance Computing
The complexity of parallel computations
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On the Architectural Requirements for Efficient Execution of Graph Algorithms
ICPP '05 Proceedings of the 2005 International Conference on Parallel Processing
A memory model for scientific algorithms on graphics processors
Proceedings of the 2006 ACM/IEEE conference on Supercomputing
A fast, parallel spanning tree algorithm for symmetric multiprocessors (SMPs)
Journal of Parallel and Distributed Computing
Scan primitives for GPU computing
Proceedings of the 22nd ACM SIGGRAPH/EUROGRAPHICS symposium on Graphics hardware
GPU computing with NVIDIA CUDA
ACM SIGGRAPH 2007 courses
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Parallel Computing
Program optimization space pruning for a multithreaded gpu
Proceedings of the 6th annual IEEE/ACM international symposium on Code generation and optimization
Fast scan algorithms on graphics processors
Proceedings of the 22nd annual international conference on Supercomputing
A GPU-based high-throughput image retrieval algorithm
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Journal of Experimental Algorithmics (JEA)
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SC '13 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis
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General purpose programming on the graphics processing units (GPGPU) has received a lot of attention in the parallel computing community as it promises to offer the highest performance per dollar. The GPUs have been used extensively on regular problems that can be easily parallelized. In this paper, we describe two implementations of List Ranking, a traditional irregular algorithm that is difficult to parallelize on such massively multi-threaded hardware. We first present an implementation of Wyllie's algorithm based on pointer jumping. This technique does not scale well to large lists due to the suboptimal work done. We then present a GPU-optimized, Recursive Helman-JaJa (RHJ) algorithm. Our RHJ implementation can rank a random list of 32 million elements in about a second and achieves a speedup of about 8-9 over a CPU implementation as well as a speedup of 3-4 over the best reported implementation on the Cell Broadband engine. We also discuss the practical issues relating to the implementation of irregular algorithms on massively multi-threaded architectures like that of the GPU. Regular or coalesced memory accesses pattern and balanced load are critical to achieve good performance on the GPU.