Results 221 to 230 of about 41,758 (261)
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Journal of Computational Chemistry, 1987
AbstractSeveral implementations of matrix multiplication (MMUL) in Fortran and VAX assembly language are discussed. On a VAX‐11/780 computer, the most efficient MMUL is achieved through vector‐scalar‐multiply‐and‐add (VSMA) operations, rather than by means of dot products.
Carlos F. Bunge, Gerardo Cisneros
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AbstractSeveral implementations of matrix multiplication (MMUL) in Fortran and VAX assembly language are discussed. On a VAX‐11/780 computer, the most efficient MMUL is achieved through vector‐scalar‐multiply‐and‐add (VSMA) operations, rather than by means of dot products.
Carlos F. Bunge, Gerardo Cisneros
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1990
Suppose that two n×n matrices A [0:n-1, 0:n-1] and B[0:n-1, 0:n-1] are to be multiplied on an SIMD hypercube to get the product matrix C where $$ C[i,j] = \sum\limits_{k = 0}^{n - 1} {A[i,k]*B[k,j],0 \le i,j < n} $$
Sanjay Ranka, Sartaj Sahni
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Suppose that two n×n matrices A [0:n-1, 0:n-1] and B[0:n-1, 0:n-1] are to be multiplied on an SIMD hypercube to get the product matrix C where $$ C[i,j] = \sum\limits_{k = 0}^{n - 1} {A[i,k]*B[k,j],0 \le i,j < n} $$
Sanjay Ranka, Sartaj Sahni
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SPARSE MATRIX–VECTOR MULTIPLICATION
2004Abstract This chapter introduces irregular algorithms and presents the example of parallel sparse matrix-vector multiplication (SpMV), which is the central operation in iterative linear system solvers. The irregular sparsity pattern of the matrix does not change during the multiplication, which may be repeated many times.
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Parallel matrix multiplication
2018 41st International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), 2018Utilizing all CPU cores available for numerical computations is a topic of considerable interest in HPC. This paper analyzes and compares four different parallel algorithms for matrix multiplication without block partitioning using OpenMP. The comparison of the algorithms is based on the achieved speed, memory bandwidth and efficient use of the cache ...
Nikola Tomikj, Marjan Gusev
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Hypercube matrix multiplication
Parallel Computing, 1993A matrix multiplication algorithm for parallel computers (hypercubes) is given. The algorithm has running times of \(O(n)\) and \(O(\log n)\) for \(n^ 2\) and \(n^ 3/2\) processors. The sub matrices are sent in a single communication to directly connected processors in the hypercube and are also involved in sequential matrix multiplication at each ...
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2018
This chapter is devoted to the study of matrix chain multiplication problem. For this problem, we consider different cost functions and present a multi-stage optimization procedure relative to a sequence of such functions.
Hassan AbouEisha +4 more
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This chapter is devoted to the study of matrix chain multiplication problem. For this problem, we consider different cost functions and present a multi-stage optimization procedure relative to a sequence of such functions.
Hassan AbouEisha +4 more
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Learning from Optimizing Matrix-Matrix Multiplication
2018 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW), 2018We describe a learning process that uses one of the simplest examples, matrix-matrix multiplication, to illustrate issues that underlie parallel high-performance computing. It is accessible at multiple levels: simple enough to use early in a curriculum yet rich enough to benefit a more advanced software developer.
Devangi N. Parikh +3 more
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The biofilm matrix: multitasking in a shared space
Nature Reviews Microbiology, 2022Hans-Curt Flemming +2 more
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Cell–extracellular matrix mechanotransduction in 3D
Nature Reviews Molecular Cell Biology, 2023Aashrith Saraswathibhatla +2 more
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