Nested parallelism on GPU: Exploring parallelization templates for irregular loops and recursive computations

Proceedings of the International Conference on Parallel Processing

Volumn 2015-December, Issue , 2015, Pages 979-988

  Li, Da ^a   Wu, Hancheng ^a   Becchi, Michela ^a  

^a University of Missouri   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CODES (SYMBOLS); FORESTRY; ITERATIVE METHODS; NETWORK MANAGEMENT; PROGRAM PROCESSORS; TREES (MATHEMATICS);

COMPUTATIONAL PATTERNS; LOAD-BALANCING MECHANISMS; NESTED PARALLELISM; PARALLELIZATIONS; RECURSIVE ALGORITHMS; RECURSIVE APPLICATIONS; RECURSIVE COMPUTATION; STREAMING MULTIPROCESSORS;

COMPUTER HARDWARE;

EID: 84976510144     PISSN: 01903918     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICPP.2015.107     Document Type: Conference Paper

References (30)

1. Y. Yang, and H. Zhou, "CUDA-NP: realizing nested thread-level parallelism in GPGPU applications, " in Proc. of PPoPP 2014.
2. J. Wang, and S. Yalamanchili, "Characterization and Analysis of Dynamic Parallelism in Unstructured GPU Applications, " in Proc. of IISWC 2014.
3. D. Li, and M. Becchi, "Deploying Graph Algorithms on GPUs: An Adaptive Solution, " in Proc. of IPDPS 2013.
4. M. Goldfarb, Y. Jo, and M. Kulkarni, "General transformations for GPU execution of tree traversals, " in Proc. of SC 2013.
5. P. Harish, and P. J. Narayanan, "Accelerating large graph algorithms on the GPU using CUDA, " in Proc. of HiPC 2007.
6. A. E. Sriyuce, et al., "Betweenness Centrality on GPUs and Heterogeneous Architectures. " in Proc. of GPGPU-6 2013.
7. N. T. Duong, et al., "Parallel PageRank computation using GPUs. " in Proc of 3rd Symp. on Information and Communication Technology, 2012.
8. J. L. Greathouse, and M. Daga, "Efficient sparse matrix-vector multiplication on GPUs using the CSR storage format. " in Proc of SC 2014.
9. "DIMACS Implementation Challenges, " http: //dimacs. rutgers. edu/Challenges/.
10. "Stanford Large Network Dataset Collection, " http: //snap. stanford. edu/data.
11. M. A. Hassaan, M. Burtscher, and K. Pingali, "Ordered vs. unordered: A comparison of parallelism and work-efficiency in irregular algorithms, " in Proc. of PPoPP 2011.
12. L. Luo, M. Wong, and W.-m. Hwu, "An effective GPU implementation of breadth-first search, " in Proc. of DAC 2010.
13. D. Merrill, M. Garland, and A. Grimshaw, "Scalable GPU graph traversal, " in Proc. of PPoPP 2012.
14. S. Hong, T. Oguntebi, and K. Olukotun, "Efficient Parallel Graph Exploration on Multi-Core CPU and GPU, " in Proc. of PACT 2011.
15. A. Gharaibeh, et al., "On Graphs, GPUs, and Blind Dating: A Workload to Processor Matchmaking Quest, " in Proc. of IPDPS 2013.
16. M. Burtscher, R. Nasre, and K. Pingali, "A quantitative study of irregular programs on GPUs, " in Proc. of IISWC 2012.
17. R. Nasre, M. Burtscher, and K. Pingali, "Data-driven versus Topology-driven Irregular Computations on GPUs, " in Proc. of IPDPS 2013.
18. R. Nasre, M. Burtscher, and K. Pingali, "Atomic-free irregular computations on GPUs, " in Proc. of GPGPU 2013.
19. R. Nasre, M. Burtscher, and K. Pingali, "Morph algorithms on GPUs, " in Proc. of PPoPP 2013.
20. S. Hong, et al., "Accelerating CUDA graph algorithms at maximum warp, " in Proc. of PPoPP 2011.
21. M. Mendez-Lojo, M. Burtscher, and K. Pingali, "A GPU implementation of inclusion-based points-to analysis, " in Proc. of PPoPP 2012.
22. J. Barnat, et al., "Computing Strongly Connected Components in Parallel on CUDA, " in Proc. of IPDPS 2011.
23. C. Shuai, et al., "Pannotia: Understanding irregular GPGPU graph applications, " in Proc of IISWC 2013.
24. F. Khorasani, et al., "CuSha: vertex-centric graph processing on GPUs, " in Proc. of HPDC 2014.
25. G. E. Blelloch, and G. W. Sabot, "Compiling collection-oriented languages onto massively parallel computers, " J. Parallel Distrib. Comput., vol. 8, no. 2, pp. 119-134, 1990.
26. G. E. Blelloch, NESL: A Nested Data-Parallel Language, Carnegie Mellon University, 1992.
27. L. Bergstrom, and J. Reppy, "Nested data-parallelism on the gpu, " in Proc. of ICFP 2012.
28. J. DiMarco, and M. Taufer, "Performance Impact of Dynamic Parallelism on Different Clustering Algorithms and the New GPU Architecture, " in Proc. of SPIE Defense, Security, and Sensing Symp. 2013.
29. A. Adinetz. "Adaptive Parallel Computation with CUDA Dynamic Parallelism, " http: //devblogs. nvidia. com/parallelforall/introductionCUDA-dynamic-parallelism/.
30. A. Adinetz. "A CUDA Dynamic Parallelism Case Study: PANDA, " http: //devblogs. nvidia. com/parallelforall/a-CUDA-dynamicparallelism-case-study-panda/.