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CORR
2011
Springer
199views Education» more  CORR 2011»
8 years 1 months ago
Fast Sparse Matrix-Vector Multiplication on GPUs: Implications for Graph Mining
Scaling up the sparse matrix-vector multiplication kernel on modern Graphics Processing Units (GPU) has been at the heart of numerous studies in both academia and industry. In thi...
Xintian Yang, Srinivasan Parthasarathy, Ponnuswamy...
ERSA
2010
199views Hardware» more  ERSA 2010»
8 years 4 months ago
Reconfigurable Sparse Matrix-Vector Multiplication on FPGAs
Cache-based, general purpose CPUs perform at a small fraction of their maximum floating point performance when executing memory-intensive simulations, such as those required for sp...
Russell Tessier, Salma Mirza, J. Blair Perot
PPSC
1997
8 years 7 months ago
Improving Memory-System Performance of Sparse Matrix-Vector Multiplication
Sparse matrix-vector multiplication is an important kernel that often runs inefficiently on superscalar RISC processors. This paper describes techniques that increase instruction-...
Sivan Toledo
CSE
2009
IEEE
8 years 9 months ago
A Comparative Study of Blocking Storage Methods for Sparse Matrices on Multicore Architectures
Sparse Matrix-Vector multiplication (SpMV) is a very challenging computational kernel, since its performance depends greatly on both the input matrix and the underlying architectur...
Vasileios Karakasis, Georgios I. Goumas, Nectarios...
PARLE
1994
8 years 9 months ago
Run-Time Optimization of Sparse Matrix-Vector Multiplication on SIMD Machines
Sparse matrix-vector multiplication forms the heart of iterative linear solvers used widely in scientific computations (e.g., finite element methods). In such solvers, the matrix-v...
Louis H. Ziantz, Can C. Özturan, Boleslaw K. ...
ICCS
2001
Springer
8 years 10 months ago
Optimizing Sparse Matrix Computations for Register Reuse in SPARSITY
Abstract. Sparse matrix-vector multiplication is an important computational kernel that tends to perform poorly on modern processors, largely because of its high ratio of memory op...
Eun-Jin Im, Katherine A. Yelick
NAA
2004
Springer
178views Mathematics» more  NAA 2004»
8 years 11 months ago
Performance Optimization and Evaluation for Linear Codes
In this paper, we develop a probabilistic model for estimation of the numbers of cache misses during the sparse matrix-vector multiplication (for both general and symmetric matrice...
Pavel Tvrdík, Ivan Simecek
HPCC
2005
Springer
8 years 11 months ago
Fast Sparse Matrix-Vector Multiplication by Exploiting Variable Block Structure
Abstract. We improve the performance of sparse matrix-vector multiplication (SpMV) on modern cache-based superscalar machines when the matrix structure consists of multiple, irregu...
Richard W. Vuduc, Hyun-Jin Moon
ISVLSI
2007
IEEE
100views VLSI» more  ISVLSI 2007»
9 years 15 days ago
Vector Processing Support for FPGA-Oriented High Performance Applications
In this paper, we propose and implement a vector processing system that includes two identical vector microprocessors embedded in two FPGA chips. Each vector microprocessor suppor...
Hongyan Yang, Shuai Wang, Sotirios G. Ziavras, Jie...
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