Computer architecture (2nd ed.): a quantitative approach
Computer architecture (2nd ed.): a quantitative approach
Performance optimizations and bounds for sparse matrix-vector multiply
Proceedings of the 2002 ACM/IEEE conference on Supercomputing
Enterprise Text Processing: A Sparse Matrix Approach
ITCC '01 Proceedings of the International Conference on Information Technology: Coding and Computing
Cell placement on graphics processing units
Proceedings of the 20th annual conference on Integrated circuits and systems design
Optimizing sparse matrix-vector multiplication using index and value compression
Proceedings of the 5th conference on Computing frontiers
Using geo-spatial session tagging for smart multicast session discovery
Proceedings of the 2009 ACM symposium on Applied Computing
Array-Structured object types for mathematical programming
JMLC'06 Proceedings of the 7th joint conference on Modular Programming Languages
| Hi-index | 0.00 |
In this paper, we consider alternate ways of storing a sparse matrix and their effect on computational speed. They involve keeping both the indices and the non-zero elements in the sparse matrix in a single data structure. These schemes thus help reduce memory system misses that occur when the usual indexing based storage schemes are used to store sparse matrices and give promising performance improvements.