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of 111
pro vyhledávání: '"Hung, Shih-Hao"'
Quantum circuit simulation is important in the evolution of quantum software and hardware. Novel algorithms can be developed and evaluated by performing quantum circuit simulations on classical computers before physical quantum computers are availabl
Externí odkaz:
http://arxiv.org/abs/2410.09326
The state vector-based simulation offers a convenient approach to developing and validating quantum algorithms with noise-free results. However, limited by the absence of cache-aware implementations and unpolished circuit optimizations, the past simu
Externí odkaz:
http://arxiv.org/abs/2406.14084
Quantum approximate optimization algorithm (QAOA) is one of the popular quantum algorithms that are used to solve combinatorial optimization problems via approximations. QAOA is able to be evaluated on both physical and virtual quantum computers simu
Externí odkaz:
http://arxiv.org/abs/2312.03019
Particle Swarm Optimization (PSO) is a stochastic technique for solving the optimization problem. Attempts have been made to shorten the computation times of PSO based algorithms with massive threads on GPUs (graphic processing units), where thread g
Externí odkaz:
http://arxiv.org/abs/2205.01313
Autor:
Wang, Chuan-Chi, Liao, Ying-Chiao, Tu, Chia-Heng, Kao, Ming-Chang, Liang, Wen-Yew, Hung, Shih-Hao
The rapid advancements of computing technology facilitate the development of diverse deep learning applications. Unfortunately, the efficiency of parallel computing infrastructures varies widely with neural network models, which hinders the explorati
Externí odkaz:
http://arxiv.org/abs/2012.01671
In this paper, we provide a fine-grain machine learning-based method, PerfNetV2, which improves the accuracy of our previous work for modeling the neural network performance on a variety of GPU accelerators. Given an application, the proposed method
Externí odkaz:
http://arxiv.org/abs/2012.00211
Akademický článek
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Publikováno v:
In Journal of Systems Architecture November 2017 81:83-91
Publikováno v:
In Pervasive and Mobile Computing December 2015 24:231-242
Publikováno v:
In Computers & Education August 2014 77:50-66