Author/Authors
duran, ahmet istanbul teknik üniversitesi fen-edebiyat - fakültesi matematik mühendisliği, İSTANBUL, TURKEY , tunçel, mehmet istanbul teknik üniversitesi - bilişim enstitüsü hesaplamalı bilim ve mühendislik, fen-edebiyat fakültesi matematik mühendisliği, İSTANBUL, Turkey , özer, hayati ünsal istanbul teknik üniversitesi - fen-edebiyat fakültesi matematik mühendisliği, İSTANBUL, Turkey , özer, hayati ünsal yıldız teknik üniversitesi - kimya-metalurji fakültesi matematik mühendisliği, İSTANBUL, Turkey
Title Of Article
Computation of Kronecker Product for Large Dense Matrices Using GPU Programming
شماره ركورد
44890
Abstract
Kronecker (tensor) product is one of the important matrix operations in numerical linear algebra and used in many scientific computational methods. As the size of dense input matrix increases, memory and computation cost become a challenging issue in this type of operation. In this work, we use GPU parallel programming in order to diminish the long wall clock time consumed by serial programming. We design a new algorithm for GPU parallel programming. We generate the necessary large dense matrices using pseudo-random number generator and implement the algorithm via CUDA threads. Moreover, we compare the performance of CPU and GPU parallel programming implementations. We discuss the advantages and limitations of GPU programming technology in this particular application.
From Page
119
NaturalLanguageKeyword
Kronecker Product , GPU Programming , Parallel Programming , Numerical Linear Algebra , Dense Matrix Operations
JournalTitle
Erciyes University Journal Of The Institute Of Science and Technology
To Page
127
JournalTitle
Erciyes University Journal Of The Institute Of Science and Technology
Link To Document