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» Optimization techniques for small matrix multiplication
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ICCS
2001
Springer
13 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
ICPP
2009
IEEE
14 years 3 days 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
13 years 3 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»
13 years 5 months 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
14 years 14 hour 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...