Results 11 to 20 of about 41,758 (261)
Fully private and secure coded matrix multiplication with colluding workers
ICT Express, 2023 In this paper, we propose a new coded computation scheme that can alleviate straggler effects in distributed computing. We consider data security and master’s privacy for matrix multiplication tasks.
Minchul Kim, Heecheol Yang, Jungwoo Lee
doaj +1 more source
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
openaire +7 more sources
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
doaj +1 more source
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
doaj +1 more source
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
doaj +1 more source
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
openaire +4 more sources
Compressed matrix multiplication [PDF]
Proceedings of the 3rd Innovations in Theoretical Computer Science Conference, 2012 We present a simple algorithm that approximates the product of n -by- n real matrices A and B . Let ‖AB‖ F denote the Frobenius norm of AB , and b
openaire +2 more sources
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
doaj +1 more source
Communications Faculty Of Science University of Ankara Series A1Mathematics and Statistics, 2017 In this paper, a new matrix multiplication is defined in Rm;nRn;pby using scalar product in Rn, where Rm;nis set of matrices of m rows and n columns. With this multiplication it has been shown that Rn;nis an algebra with unit. By considering this new multiplication we define eigenvalues and eigen vectors of square n n matrix A and also present some ...
KEÇİLİOĞLU, Osman, GÜNDOĞAN, Halit
openaire +2 more sources
Hierarchical Coded Matrix Multiplication [PDF]
IEEE Transactions on Information Theory, 2019 In distributed computing systems slow working nodes, known as stragglers, can greatly extend finishing times. Coded computing is a technique that enables straggler-resistant computation. Most coded computing techniques presented to date provide robustness by ensuring that the time to finish depends only on a set of the fastest nodes.
Shahrzad Kianidehkordi +2 more
openaire +4 more sources