Fast Matrix Multiplication with Big Sparse Data

1. Di Felice, P., A. Agnifili, E. Clementini. Data Structures for Compact Sparse Matrices Representation. - J. Adv. Eng. Software, Vol. 11, 1989, No 2, pp. 75-83.10.1016/0141-1195(89)90064-8Search in Google Scholar

2. Abadi, D. J. Column-Stores for Wide and Sparse Data. - In: Proc. of 3rd Biennial Conference on Innovative Data Systems Research (CIDR), January 2007, pp. 1-6.Search in Google Scholar

3. Neelima, B., S. R. Prakash. Effective Sparse Matrix Representation for the GPU Architectures. - Int. J. of Computer Science, Engineering and Applications (IJCSEA), Vol. 2, 2012, No 2, pp. 151-165.10.5121/ijcsea.2012.2213Search in Google Scholar

4. Yuster, R., U. Zwick. Fast Sparse Matrix Multiplication. - J. ACM Transactions on Algorithms (TALG), Vol. 1, 2005, No 1, pp. 2-13.10.1145/1077464.1077466Search in Google Scholar

5. Dean, J., S. Ghemawat. Map Reduce: Simplified Data Processing on Large Clusters. - Communications of the ACM, Vol. 51, 2008, No 1, pp. 107-113.10.1145/1327452.1327492Search in Google Scholar

6. White, T. H. The Definitive Guide. O’Reilly Media, USA, 2009.Search in Google Scholar

7. Buluc, A., J. R. Gilbert. Parallel Sparse Matrix-Matrix Multiplication and Indexing: Implementation and Experiments. - Siam J. Sci. Comput., Vol. 34, 2011, No 4, pp. C170-C191.10.1137/110848244Search in Google Scholar

8. Ballard, G., A. Bulluc, J. Demmel, L. Grigori, B. Lipshitz, O. Schwartz, S. Toledo. Communication Optimal Parallel Multiplication of Sparse Random Matrices. - In: Proc. of 25th Annual ACM Symposium on Parallelism in Algorithms and Architectures, New York, July 2013, pp. 222-231.10.1145/2486159.2486196Search in Google Scholar

9. Smith, S., N. Ravindran, N. D. Sidiropoulos, G. Karypis. SPLATT: Efficient and Parallel Sparse Tensor-Matrix Multiplication. - In: Proc. of 29th IEEE International Parallel & Distributed Processing Symposium, May 2015.10.1109/IPDPS.2015.27Search in Google Scholar

10. Sun, Z., T. Li, N. Rishe. Large-Scale Matrix Factorization using Map Reduce. - In: Proc. of International Conference on Data Mining Workshops, December 2010, pp. 1242-1248.10.1109/ICDMW.2010.155Search in Google Scholar

11. Seo, S., E. J. Yoon, J. Kim, S. Jin, J. S. Kim, S. Maeng. HAMA: An Efficient Matrix Computation with the Map Reduce Framework. - In: Proc. of IEEE 2nd International Conference on Cloud Computing Technology and Science (Cloud Com), November 2010, pp. 721-726.10.1109/CloudCom.2010.17Search in Google Scholar

12. Seo, S., I. Jang, K. Woo, I. Kim, J. S. Kim, S. Maeng. HPMR: Prefetching and Pre-Shuffling in Shared Map Reduce Computation Environment. – In: Proc. of 11th IEEEInternational Conference on Cluster Computing, New Orleans, August 2009, pp. 1-8.10.1109/CLUSTR.2009.5289171Search in Google Scholar

13. Myung, J., S. Lee. Matrix Chain Multiplication via Multi Way Join Algorithms in Mapreduce.– In: Proc. of 6th International Conference on Ubiquitous Information Management and Communication, Article No 53, February 2012.10.1145/2184751.2184817Search in Google Scholar

14. Zheng, J. H., L. J. Zhang, R. Zhu, K. Ning, D. Liu. Parallel Matrix Multiplication Algorithm Based on Vector Linear Combination Using Map Reduce. – In: Proc. of IEEE 11th World Congress on Services, July 2013, pp.193-200.10.1109/SERVICES.2013.67Search in Google Scholar

15. Ceccarello, M., F. Silvestr i. Experimental Evaluation of Multi-Round Matrix Multiplication on Map Reduce. – In: Proc. of ALENEX’15 Meeting on Algorithm Engineering & Experiments, Society for Industrial and Applied Mathematics Philadelphia, January 2015, pp. 119-132.10.1137/1.9781611973754.11Search in Google Scholar

16. Choi, J., J. J. Dongarra, R. Pozo, D. W. Walker. Sca LAPACK: A Scalable Linear Algebra Library for Distributed Memory Concurrent Computers. – In Proc. of 4th Sysmposium on the Frontiers of Massively Parallel Computation, IEEE, October 1992, pp. 120-127.Search in Google Scholar

17. Bosilca, G., A. Bouteiller , A. Danalis, T. Herault, P. Lemarinier, J. Dongarra. DAGu E: A Generic Distributed DAG Engine for High Performance Computing. – J. Parallel Computing, Vol. 38, 2010, No 1-2, pp. 37-51.10.1016/j.parco.2011.10.003Search in Google Scholar

18. Qian, Z., X. Chen, N. Kang, M. Chen, Y. Yu, T. Mosc ibroda, Z. Zhang. Mad LINQ: Large-Scale Distributed Matrix Computation for the Cloud. – In Proc. of 7th ACM European Conference on Computer Systems Euro Sys’2012, Berne, Switzerland, April 2012, pp. 197-210.10.1145/2168836.2168857Search in Google Scholar