Splitting Matching Pursuit Method for Reconstructing Sparse Signal in Compressed Sensing by Liu Jing, Han ChongZhao, Yao XiangHua, Lian Feng

“…The Merging, Estimation and Pruning steps are carried out for each split set independently, which makes it especially suitable for parallel computation. The proposed SMP method is then extended to more practical condition, e.g. the direction of arrival (DOA) estimation problem in phased array radar system using compressed sensing. …”
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BIT*+TD3 Hybrid Algorithm for Energy-Efficient Path Planning of Unmanned Surface Vehicles in Complex Inland Waterways by Yunze Xie, Yiping Ma, Yiming Cheng, Zhiqian Li, Xiaoyu Liu

“…Furthermore, it incorporates a hydrodynamics-based energy consumption model and multi-threaded parallel computation to enhance computational efficiency. …”
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High-performance computing for static security assessment of large power systems by Venkateswara Rao Kagita, Sanjaya Kumar Panda, Ram Krishan, P. Deepak Reddy, Jabba Aswanth

“…To enhance the accuracy, AC load flow is used, and parallel computation of load flow is done simultaneously, with efficient screening and ranking of the critical contingencies. …”
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An Automatic Generalization Method of a Block-Based Digital Depth Model Based on Surface Curvature Features by Dong Wang, Jian Dong, Lulu Tang, Mengkai Ma, Tian Xie

“…By integrating a multi-threaded parallel computation model, an efficient automated generalization workflow that encompasses data partitioning, fitting, computation, processing, and integration of the DDM is ultimately constructed. …”
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RM-MOCO: A Fast-Solving Model for Neural Multi-Objective Combinatorial Optimization Based on Retention by Huiqing Wei, Fei Han, Qing Liu, Henry Han

“…During model training, a parallel computation of retention is applied, allowing for fast parallel training. …”
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DGAT: a dynamic graph attention neural network framework for EEG emotion recognition by Shihang Ding, Kaixuan Wang, Wenhao Jiang, Cong Xu, Hongjian Bo, Lin Ma, Haifeng Li

“…This framework dynamically learns the relationships between different channels by utilizing dynamic adjacency matrices and a multi-head attention mechanism, allowing for the parallel computation of multiple attention heads. This approach reduces reliance on specific adjacency structures while enabling the model to learn information in different subspaces, significantly improving the accuracy of emotion recognition from EEG signals.ResultsExperiments conducted on the EEG emotion datasets SEED and DEAP demonstrate that DGAT achieves higher emotion classification accuracy in both subject-dependent and subject-independent scenarios compared to other models. …”
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ReScConv-xLSTM: An improved xLSTM model with spatiotemporal feature extraction capability for remaining useful life prediction of Aero-engine by Mingxing Huang, Lanying Yang, Gang Jiang, Xingan Hao, Hong Lu, Hang Luo, Peng Wang, Jinyang Li

“…Although deep learning models based on LSTM and Transformer have achieved significant results in this field, these models typically only extract temporal features, neglecting spatial features, and struggle with parallel computation, leading to a bottleneck in RUL prediction performance. …”
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Measurement of the Efficiency of Parallel Genetic Algorithm for Compress and Decompression of Fractal Imaging Using Multiple Computers by Shahla Abdul Qadir

“…The research aims at using the Parallel Genetic Algorithm (PGA) by the technology of the (Manager/Worker) in parallel computers to obtain  best and quickest compress for images by  coding the site of the searching domain block with a Gray code and a fitness function that minimizes the space  between the matching of the current range block with the searching  domain block  in order  to choose  a protection strategy and compress of high accuracy of  images . …”
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Acceleration of boundary element calculations for closed domain using nonlinear form functions and CUDA technology by S. S. Sherbakov, M. M. Polestchuk

“…The dependences of acceleration of parallel  computations  as  compared  with  sequential  ones  were explored  for  different  numbers  of  boundary elements  and  computational  nodes.  …”
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Collaborative Optimization Strategy for Dependent Task Offloading in Vehicular Edge Computing by Xiting Peng, Yandi Zhang, Xiaoyu Zhang, Chaofeng Zhang, Wei Yang

“…Moreover, these tasks are often interdependent, preventing parallel computation and severely prolonging completion times, which results in substantial energy consumption. …”
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A Reconfigurable Coarse-to-Fine Approach for the Execution of CNN Inference Models in Low-Power Edge Devices by Auangkun Rangsikunpum, Sam Amiri, Luciano Ost

“…To efficiently deploy CNN inference models on resource-constrained edge devices, field programmable gate arrays (FPGAs) have become a viable processing solution because of their unique hardware characteristics, enabling flexibility, parallel computation and low-power consumption. In this regard, this work proposes an FPGA-based dynamic reconfigurable coarse-to-fine (C2F) inference of CNN models, aiming to increase power efficiency and flexibility. …”
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Computing with electromagnetic fields rather than binary digits: a route towards artificial general intelligence and conscious AI by Johnjoe McFadden

“…According to the theory, non-conscious brain processing occurs solely within the EM field-insensitive digital neuronal network, enabling fast, parallel computations, but cannot form complex, integrated concepts, so it is limited to specialised functions necessary for tasks like motor coordination. …”
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Input/Output analysis and optimization for GRAPES regional model by Yang Bin, Wang Jingyu, Liu Weiguo, Cai Huiyi, Yu Fei, Deng Liantang, Huang Liping

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Alquimia v1.0: a generic interface to biogeochemical codes – a tool for interoperable development, prototyping and benchmarking for multiphysics simulators by S. Molins, B. J. Andre, J. N. Johnson, J. N. Johnson, G. E. Hammond, B. N. Sulman, K. Lipnikov, M. S. Day, J. J. Beisman, D. Svyatsky, H. Deng, P. C. Lichtner, C. I. Steefel, J. D. Moulton

“…Alquimia relies on a single-cell approach that permits operator splitting coupling and parallel computation. We describe the implementation in Alquimia of two widely used open-source codes that perform geochemical calculations: PFLOTRAN and CrunchFlow. …”
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Fused-MemBrain: a spiking processor combining CMOS and self-assembled memristive networks by Davide Cipollini, Hugh Greatorex, Michele Mastella, Elisabetta Chicca, Lambert Schomaker

“…In this way, a memristive self-assembled material can cheaply and efficiently replace the synaptic connections between CMOS neuron implementations in neuromorphic hardware, enhancing the capability of massively parallel computation. The fusion of CMOS circuits with a memristive ‘plexus’ allows information transfer without requiring engineered synapses, which typically consume significant area. …”
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Modified triple modular redundancy based fault-tolerant three-phase matrix converter design with AI driven diagnostic capabilities by Faizan Ahmad, Mohaira Ahmad, Faisal Hayat, Sami ud Din, Muhammad Adnan, Arslan Ahmed Amin

“…The MATLAB/Simulink results indicate that the proposed system provides 99.9 % reliability and ANN's parallel computations allow the system to offer fast fault detection. …”
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Low-dose computed tomography image denoising using pixel level non-local self-similarity prior with non-local means for healthcare informatics by Dawa Chyophel Lepcha, Bhawna Goyal, Ayush Dogra, Krunal Vaghela, Ashish Singh, K. S. Ravi Kumar, Durga Prasad Bavirisetti

“…This revised approach uses discrete neighbourhood filtering properties to enable efficient, vectorized, and parallel computation on modern shared-memory platforms thereby reducing computational complexity. …”
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A special machine for solving NP-complete problems by Jin Xu, Le Yu, Huihui Yang, Siyuan Ji, Pu Wu, Yu Zhang, Anqi Yang, Quanyou Li, Haisheng Li, Enqiang Zhu, Xiaolong Shi, Zehui Shao, Huang Leng, Xiaoqing Liu

“…The EPC employs a hybrid serial/parallel computational model, structured around four main subsystems: a converting system, an input/output system, and an operating system. …”
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SCAT: Shift Channel Attention Transformer for Remote Sensing Image Super-Resolution by Yingdong Kang, Xuemin Zhang, Shaoju Wang, Guang Jin

“…This design enables parallel computation of self-attention across multiple heads while ensuring robust cross-channel connections, thereby enhancing the global context modeling capabilities of the network. …”
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Deep neural network based distribution system state estimation using hyperparameter optimization by Gergő Békési, Lilla Barancsuk, Bálint Hartmann

“…The proposed non-iterative algorithm, combined with the parallel computation capabilities of deep neural networks utilizing GPU, resulted in four orders of magnitude improvement in runtime. …”
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