Domain-Specific Modeling for Rapid Energy Estimation of Reconfigurable Architectures
The Journal of Supercomputing
Sparse Matrix-Vector multiplication on FPGAs
Proceedings of the 2005 ACM/SIGDA 13th international symposium on Field-programmable gate arrays
The use of configurable computing for computational kernels in scientific simulations
Future Generation Computer Systems
The use of configurable computing for computational kernels in scientific simulations
Future Generation Computer Systems
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In this paper we report on our experimentation with the use of FPGA-based system to solve the irregular computation problem of evaluating y = Ax when the matrix A is sparse. The main features of our matrix-vector multiplication algorithm are (i) an organization of the operations tosuit the FPGA-based system ability in processing a stream of data, and (ii) the use of distributed arithmetic technique together with an efficient scheduling heuristic to exploit the inherent parallelism in the matrix-vector multiplication problem. The performance of our algorithm has been evaluated with an implementation on the Pamette FPGA-based system.