Results 31 to 40 of about 2,725,619 (370)
ASIC Implementation of Bit Matrix Multiplier [PDF]
E3S Web of Conferences, 2023 In computer science and digital electronics, a bit matrix multiplier (BMM) is a mathematical operation that is used to quickly multiply binary matrices.
Reddy K. Swetha +4 more
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Exploiting Multiple Levels of Parallelism in Sparse Matrix-Matrix Multiplication [PDF]
SIAM Journal on Scientific Computing, 2016 Sparse matrix-matrix multiplication (or SpGEMM) is a key primitive for many high-performance graph algorithms as well as for some linear solvers, such as algebraic multigrid. The scaling of existing parallel implementations of SpGEMM is heavily bound by communication.
Azad, Ariful +7 more
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Evaluating Spatial Accelerator Architectures with Tiled Matrix-Matrix Multiplication [PDF]
IEEE Transactions on Parallel and Distributed Systems, 2021 There is a growing interest in custom spatial accelerators for machine learning applications. These accelerators employ a spatial array of processing elements (PEs) interacting via custom buffer hierarchies and networks-on-chip.
G. Moon +5 more
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AN ORDER-P TENSOR MULTIPLICATION WITH CIRCULANT STRUCTURE
Barekeng, 2023 Research on mathematical operations involving multidimensional arrays or tensors has increased along with the growing applications involving multidimensional data analysis. The -product of order- tensor is one of tensor multiplications.
Itsar Mangngiri +2 more
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Adaptive Private Distributed Matrix Multiplication [PDF]
IEEE Transactions on Information Theory, 2021 We consider the problem of designing codes with flexible rate (referred to as rateless codes), for private distributed matrix-matrix multiplication. A master server owns two private matrices $\mathbf {A}$ and $\mathbf {B}$ and hires worker nodes to help ...
Rawad Bitar +2 more
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Local Re-Encoding for Coded Matrix Multiplication
IEEE Open Journal of the Communications Society, 2022 Matrix multiplication is a fundamental operation in various algorithms for big data analytics and machine learning. As the size of the dataset increases rapidly, it is now a common practice to distribute the computation on multiple servers. As straggling
Xian Su +4 more
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GE-SpMM: General-Purpose Sparse Matrix-Matrix Multiplication on GPUs for Graph Neural Networks [PDF]
International Conference for High Performance Computing, Networking, Storage and Analysis, 2020 The acceleration of Graph Neural Networks (GNNs) requires efficient and framework-compatible Sparse-Dense Matrix-Matrix Multiplication (SpMM). From the compatibility perspective, the sophisticated sparse matrix representations in state-of-the-art SpMM ...
Guyue Huang +3 more
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On fast multiplication of a matrix by its transpose [PDF]
, 2020 We present a non-commutative algorithm for the multiplication of a 2x2-block-matrix by its transpose using 5 block products (3 recursive calls and 2 general products) over C or any finite field.We use geometric considerations on the space of bilinear ...
Dumas, Jean-Guillaume +2 more
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Hyper-systolic matrix multiplication [PDF]
Parallel Computing, 2001 A novel parallel algorithm for matrix multiplication is presented. The hyper-systolic algorithm makes use of a one-dimensional processor abstraction. The procedure can be implemented on all types of parallel systems. It can handle matrix-vector multiplications as well as transposed matrix products.
Lippert, Th. +3 more
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Parallel Transitive Closure Algorithm for Heterogeneous Architecture [PDF]
Jisuanji gongcheng, 2021 The traditional method for obtaining the transitive closure of the graphs faces the large amount of calculation and long calculation time. In order to improve the computing speed of the transitive closure algorithm for dealing with large amounts of data,
XIAO Han, GUO Baoyun, LI Cailin, ZHOU Qinglei
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