Towards improved parallelism through order reduction of accessing data in nD matrices
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Date
2014
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Springer
Abstract
This paper encompasses the presentation of an enhanced approach with the capacity to reduce the time complexity of accessing nodes in m-dimensional matrices from to . The accomplishment of this process is attained by the serialization of nD (nD) matrices to single-dimensional arrays followed by the access of nodes accordingly. Linear representation of nD matrix data structure induces a superior parallelism of matrix calculations over dense, parallel core micro-architecture computers, including NVIDIA GPGPU Supercomputing and Intel Xeon Phi processing boards. This approach is feasibly implemented as the core of matrix data representation in Math software such as Matlab, Mathematica and Maple, in IDEs for more optimized code generation and in Parallel Computing Libraries such as CUBLAS and Magma.
Description
Keywords
Matrix serialization / Deserialization, Order reduction, Multi-dimensional matrices
Turkish CoHE Thesis Center URL
Citation
0
WoS Q
Q2
Scopus Q
Q2
Source
Volume
70
Issue
2
Start Page
977
End Page
986