Sciweavers

131 search results - page 3 / 27
» Optimization techniques for small matrix multiplication
Sort
View
ICCS
2001
Springer
15 years 4 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
128
Voted
ICPP
2009
IEEE
15 years 7 months ago
Perfomance Models for Blocked Sparse Matrix-Vector Multiplication Kernels
—Sparse Matrix-Vector multiplication (SpMV) is a very challenging computational kernel, since its performance depends greatly on both the input matrix and the underlying architec...
Vasileios Karakasis, Georgios I. Goumas, Nectarios...
MFCS
2010
Springer
14 years 11 months ago
Evaluating Non-square Sparse Bilinear Forms on Multiple Vector Pairs in the I/O-Model
We consider evaluating one bilinear form defined by a sparse Ny × Nx matrix A having h entries on w pairs of vectors The model of computation is the semiring I/O-model with main ...
Gero Greiner, Riko Jacob
CORR
2010
Springer
225views Education» more  CORR 2010»
15 years 16 days ago
Sensing Matrix Optimization for Block-Sparse Decoding
Recent work has demonstrated that using a carefully designed sensing matrix rather than a random one, can improve the performance of compressed sensing. In particular, a welldesign...
Kevin Rosenblum, Lihi Zelnik-Manor, Yonina C. Elda...
ICCS
2009
Springer
15 years 7 months ago
Generating Empirically Optimized Composed Matrix Kernels from MATLAB Prototypes
The development of optimized codes is time-consuming and requires extensive architecture, compiler, and language expertise, therefore, computational scientists are often forced to ...
Boyana Norris, Albert Hartono, Elizabeth R. Jessup...