Results 61 to 70 of about 2,725,619 (370)
Multiplication of medium-density matrices using TensorFlow on multicore CPUs
Tehnički Glasnik, 2019 Matrix multiplication is an essential part of many applications, such as linear algebra, image processing and machine learning. One platform used in such applications is TensorFlow, which is a machine learning library whose structure is based on dataflow
Siraphob Theeracheep +1 more
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An Approximate GEMM Unit for Energy-Efficient Object Detection
Sensors, 2021 Edge computing brings artificial intelligence algorithms and graphics processing units closer to data sources, making autonomy and energy-efficient processing vital for their design.
Ratko Pilipović +4 more
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Faster Replacement Paths [PDF]
, 2010 The replacement paths problem for directed graphs is to find for given nodes s and t and every edge e on the shortest path between them, the shortest path between s and t which avoids e.
Williams, Virginia Vassilevska
core +2 more sources
A New Parallel Matrix Multiplication Method Adapted on Fibonacci Hypercube Structure [PDF]
Journal of Sciences, Islamic Republic of Iran, 2010 The objective of this study was to develop a new optimal parallel algorithm for matrix multiplication which could run on a Fibonacci Hypercube structure. Most of the popular algorithms for parallel matrix multiplication can not run on Fibonacci Hypercube
L Jokar
doaj
FIELD FORMATION OF CIRCULANT MATRIX
Barekeng, 2020 The axioms of fields satisfy over sets of numbers such as , , and . Generally, a set matrix is not commutative for binary multiplication properties, such that cannot satisfy of field axioms.
Mahfudz Reza Fahlevi
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Digital in-memory stochastic computing architecture for vector-matrix multiplication
Frontiers in Nanotechnology, 2023 The applications of the Artificial Intelligence are currently dominating the technology landscape. Meanwhile, the conventional Von Neumann architectures are struggling with the data-movement bottleneck to meet the ever-increasing performance demands of ...
Shady Agwa, Themis Prodromakis
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Solving Sparse Linear Systems Faster than Matrix Multiplication [PDF]
ACM-SIAM Symposium on Discrete Algorithms, 2020 Can linear systems be solved faster than matrix multiplication? While there has been remarkable progress for the special cases of graph-structured linear systems, in the general setting, the bit complexity of solving an n × n linear system Ax = b is Õ(nω)
Richard Peng, S. Vempala
semanticscholar +1 more source
Runtime Adaptive Matrix Multiplication for the SW26010 Many-Core Processor
IEEE Access, 2020 The study of matrix multiplication on the emerging SW26010 processor is highly significant for many scientific and engineering applications. The state-of-the-art work from the swBLAS library, called SWMM, focuses mainly on the infrequent case involving ...
Zheng Wu +4 more
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BISMO: A Scalable Bit-Serial Matrix Multiplication Overlay for Reconfigurable Computing
, 2018 Matrix-matrix multiplication is a key computational kernel for numerous applications in science and engineering, with ample parallelism and data locality that lends itself well to high-performance implementations.
Rasnayake, Lahiru +2 more
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Geometric rank of tensors and subrank of matrix multiplication [PDF]
Electron. Colloquium Comput. Complex., 2020 Motivated by problems in algebraic complexity theory (e.g., matrix multiplication) and extremal combinatorics (e.g., the cap set problem and the sunflower problem), we introduce the geometric rank as a new tool in the study of tensors and hypergraphs. We
Swastik Kopparty +2 more
semanticscholar +1 more source