Ankitkumar Patel¹, Srivathsan Vasudevan^1,*, Satya Bulusu^2,*

CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 3803-3818, 2024, DOI:10.32604/cmc.2024.052851

Abstract Molecular Dynamics (MD) simulation for computing Interatomic Potential (IAP) is a very important High-Performance Computing (HPC) application. MD simulation on particles of experimental relevance takes huge computation time, despite using an expensive high-end server. Heterogeneous computing, a combination of the Field Programmable Gate Array (FPGA) and a computer, is proposed as a solution to compute MD simulation efficiently. In such heterogeneous computation, communication between FPGA and Computer is necessary. One such MD simulation, explained in the paper, is the (Artificial Neural Network) ANN-based IAP computation of gold (Au₁₄₇ & Au₃₀₉) nanoparticles. MD simulation calculates the forces… More >

Fangzhou He^1,3, Ke Ding^1,2, Dingjiang Yan³, Jie Li^3,*, Jiajun Wang^1,2, Mingzhe Chen^1,2

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 3021-3045, 2024, DOI:10.32604/cmc.2024.053632

Abstract Massive computational complexity and memory requirement of artificial intelligence models impede their deployability on edge computing devices of the Internet of Things (IoT). While Power-of-Two (PoT) quantization is proposed to improve the efficiency for edge inference of Deep Neural Networks (DNNs), existing PoT schemes require a huge amount of bit-wise manipulation and have large memory overhead, and their efficiency is bounded by the bottleneck of computation latency and memory footprint. To tackle this challenge, we present an efficient inference approach on the basis of PoT quantization and model compression. An integer-only scalar PoT quantization (IOS-PoT)… More >

Ching‐Han Chen^a, Ching‐Yi Chen^b, Nai‐Yuan Liu^a

Intelligent Automation & Soft Computing, Vol.25, No.2, pp. 375-384, 2019, DOI:10.31209/2019.100000099

Abstract This study introduces a dynamic gesture recognition system applicable in IPTV remote control. In this system, we developed a hardware accelerator for realtime moving object detection. It is able to detect the position of hand block in each frame at high speed. After acquiring the information of hand block, the system can capture the robust dynamic gesture feature with the moving trail of hand block in the continuous images, and input to FNN classifier for starting recognition process. The experimental results show that our method has a good recognition performance, and more applicable to real More >