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» Group-theoretic Algorithms for Matrix Multiplication
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ISPDC
2010
IEEE
13 years 7 months ago
Pretty Good Accuracy in Matrix Multiplication with GPUs
—With systems such as Road Runner, there is a trend in super computing to offload parallel tasks to special purpose co-processors, composed of many relatively simple scalar proc...
Matthew Badin, Lubomir Bic, Michael B. Dillencourt...
PARLE
1994
13 years 12 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. ...
ARC
2010
Springer
387views Hardware» more  ARC 2010»
14 years 3 months ago
Optimising Memory Bandwidth Use for Matrix-Vector Multiplication in Iterative Methods
Computing the solution to a system of linear equations is a fundamental problem in scientific computing, and its acceleration has drawn wide interest in the FPGA community [1–3]...
David Boland, George A. Constantinides
ICASSP
2009
IEEE
13 years 6 months ago
Probabilistic matrix tri-factorization
Nonnegative matrix tri-factorization (NMTF) is a 3-factor decomposition of a nonnegative data matrix, X USV , where factor matrices, U, S, and V , are restricted to be nonnegativ...
Jiho Yoo, Seungjin Choi
ICCD
2005
IEEE
246views Hardware» more  ICCD 2005»
14 years 5 months ago
H-SIMD Machine: Configurable Parallel Computing for Matrix Multiplication
FPGAs (Field-Programmable Gate Arrays) are often used as coprocessors to boost the performance of dataintensive applications [1, 2]. However, mapping algorithms onto multimillion-...
Xizhen Xu, Sotirios G. Ziavras