Faster matrix-vector multiplication on GeForce 8800GTX

Recently a GPU has acquired programmability to perform general purpose computation fast by running ten thousands of threads concurrently. This paper presents a new algorithm for dense matrix-vector multiplication on NVIDIA CUDA architecture. The experimental results on GeForce 8800GTX show that the proposed algorithm runs maximum 15.69 (resp., 32.88) times faster than the sgemv routine in

• Type: Conference
• Year: 2008
• Where: IPPS
• Authors: N. Fujimoto
• Keywords: Dense Matrix-vector Multiplication, Distributed And Parallel Computing, General Purpose Computation, IPPS 2008, NVIDIA CUDA Architecture