Discovering faster matrix multiplication algorithms with reinforcement learning. [PDF]
Nature, 2022 Improving the efficiency of algorithms for fundamental computations can have a widespread impact, as it can affect the overall speed of a large amount of computations.
Fawzi A +12 more
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Photonic matrix multiplication lights up photonic accelerator and beyond. [PDF]
Light Sci Appl, 2022 Matrix computation, as a fundamental building block of information processing in science and technology, contributes most of the computational overheads in modern signal processing and artificial intelligence algorithms.
Zhou H +11 more
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Optimal sequence for chain matrix multiplication using evolutionary algorithm [PDF]
PeerJ Computer Science, 2021 The Chain Matrix Multiplication Problem (CMMP) is an optimization problem that helps to find the optimal way of parenthesization for Chain Matrix Multiplication (CMM).
Umer Iqbal +7 more
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DGEMM on Integer Matrix Multiplication Unit [PDF]
The international journal of high performance computing applications, 2023 Deep learning hardware achieves high throughput and low power consumption by reducing computing precision and specializing in matrix multiplication. For machine learning inference, fixed-point value computation is commonplace, where the input and output ...
Hiroyuki Ootomo +2 more
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Solving Linear Programs in the Current Matrix Multiplication Time [PDF]
Journal of the ACM, 2021 This article shows how to solve linear programs of the form minAx=b,x≥ 0 c⊤ x with n variables in time O*((nω+n2.5−α/2+n2+1/6) log (n/δ)), where ω is the exponent of matrix multiplication, α is the dual exponent of matrix multiplication, and δ is the ...
Michael B. Cohen, Yin Tat Lee, Zhao Song
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In‐Memory Vector‐Matrix Multiplication in Monolithic Complementary Metal–Oxide–Semiconductor‐Memristor Integrated Circuits: Design Choices, Challenges, and Perspectives [PDF]
Advanced Intelligent Systems, 2020 The low communication bandwidth between memory and processing units in conventional von Neumann machines does not support the requirements of emerging applications that rely extensively on large sets of data. More recent computing paradigms, such as high
Amirali Amirsoleimani +8 more
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Locally Encoded Secure Distributed Batch Matrix Multiplication [PDF]
EntropyWe study the problem of locally encoded secure distributed batch matrix multiplication (LESDBMM), where M pairs of sources each encode their respective batches of massive matrices and distribute the generated shares to a subset of N worker nodes.
Haobo Jia, Zhuqing Jia
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SpArch: Efficient Architecture for Sparse Matrix Multiplication [PDF]
International Symposium on High-Performance Computer Architecture, 2020 Generalized Sparse Matrix-Matrix Multiplication (SpGEMM) is a ubiquitous task in various engineering and scientific applications. However, inner product based SpGEMM introduces redundant input fetches for mismatched nonzero operands, while outer product ...
Zhekai Zhang +3 more
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Hybrid optimization technique for matrix chain multiplication using Strassen’s algorithm [version 2; peer review: 3 approved, 1 approved with reservations] [PDF]
F1000ResearchBackground Matrix Chain Multiplication (MCM) is a fundamental problem in computational mathematics and computer science, often encountered in scientific computing, graphics, and machine learning.
Srinivasarao Thota +2 more
doaj +2 more sources
Acceleration of Approximate Matrix Multiplications on GPUs [PDF]
Entropy, 2023 Matrix multiplication is important in various information-processing applications, including the computation of eigenvalues and eigenvectors, and in combinatorial optimization algorithms.
Takuya Okuyama +3 more
doaj +2 more sources