Results 1 to 10 of about 5,075,844 (278)
Analysis on the AES Implementation with Various Granularities on Different GPU Architectures
Advances in Electrical and Electronic Engineering, 2017 The Advanced Encryption Standard (AES) is One of the most popular symmetric block cipher because it has better efficiency and security. The AES is computation intensive algorithm especially for massive transactions.
Ahmed Awadalla Abdelrahman +2 more
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An efficient quantum circuit implementation of Shor’s algorithm for GPU accelerated simulation
AIP AdvancesIn this study, we introduce a novel implementation of Shor’s algorithm specifically designed for the Graphics Processing Unit (GPU) acceleration framework.
XinJian Tan, Peng Gao
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Journal of Low Power Electronics and ApplicationsThis study presents a comprehensive performance evaluation of field-programmable gate array (FPGA), graphics processing unit (GPU), and central processing unit (CPU) platforms for implementing finite impulse response (FIR) filters in semiconductor-based ...
Muhammet Arucu, Teodor Iliev
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Processing Time Analysis and Estimation for 3-D Applications
IEEE Access, 2014 The performance analysis of a graphics processing unit (GPU) is important for analyzing and fine tuning current and future graphics processors as well as for comparing the performance of different architectures.
Joseph A. Issa
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Efficient Tsunami Modeling on Adaptive Grids with Graphics Processing Units (GPUs)
CoRR, 2019 Solving the shallow water equations efficiently is critical to the study of natural hazards induced by tsunami and storm surge, since it provides more response time in an early warning system and allows more runs to be done for probabilistic assessment where thousands of runs may be required.
Xinsheng Qin +2 more
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Symmetric Tridiagonal Eigenvalue Solver Across CPU Graphics Processing Unit (GPU) Nodes
Applied SciencesIn this work, an improved and scalable implementation of Cuppen’s algorithm for diagonalizing symmetric tridiagonal matrices is presented. This approach uses a hybrid-heterogeneous parallelization technique, taking advantage of GPU and CPU in a ...
Erika Hernández-Rubio +5 more
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Fast computation of MadGraph amplitudes on graphics processing unit (GPU) [PDF]
The European Physical Journal C, 2013 37 pages, 12 ...
Hagiwara, K. +4 more
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IEEE AccessAdvanced memory optimization techniques are reviewed to enhance the performance of Convolutional Neural Networks (CNNs) and Spiking Neural Networks (SNNs) on hardware accelerators, addressing the real-world challenges in medical imaging.
N. Srikanth Prasad, S. Sundar
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GPU-Accelerated Parallel FDTD on Distributed Heterogeneous Platform
International Journal of Antennas and Propagation, 2014 This paper introduces a (finite difference time domain) FDTD code written in Fortran and CUDA for realistic electromagnetic calculations with parallelization methods of Message Passing Interface (MPI) and Open Multiprocessing (OpenMP). Since both Central
Ronglin Jiang +5 more
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A Simulation Accelerating Method Based on CUDA with Kepler GPU
Dianxin kexue, 2015 An accelerating method based on CUDA（compute unified device architecture）with Kepler GPU（graphics processing unit）was proposed to speed up the DFT（discrete Fourier transform）processing in the communication simulation platform.Based on this method，the ...
Bingjun Han, Shiming Huang, Ying Du
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