Combination of multigrid with constraint data for inverse problem of nonlinear diffusion equation by Liu, Tao, Ouyang, Di, Guo, Lianjun, Qiu, Ruofeng, Qi, Yunfei, Xie, Wu, Ma, Qiang, Liu, Chao

“…Numerical results demonstrate the computational performance of this method. The proposed combination strategy displays remarkable capabilities in reducing noise, avoiding local minima, and accelerating convergence. …”
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Engineering a Programming Language: The Type and Class System of Sather by Szyperski, C, Omohundro, S, Murer, S

“…It attempts to support a powerful object-oriented paradigm without sacrificing either the computational performance of traditional procedural languages or support for safety and correctness checking. …”

Optimal scheduling of fighter aircraft maintenance by Cho, Philip Y

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Constraint-aware configurable system-on-chip design for embedded computing by Alok Prakash

“…Experimental results based on applications from widely-used benchmark suites confirm that deploying custom instructions identified in this way can improve compute performance by up to 65%. The instruction level parallelism (ILP) has also been exploited to further improve the compute performance by identifying profitable coarse-grained custom instructions. …”
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SMGen: A Generator of Synthetic Models of Biochemical Reaction Networks by Simone G. Riva, Paolo Cazzaniga, Marco S. Nobile, Simone Spolaor, Leonardo Rundo, Daniela Besozzi, Andrea Tangherloni

“…Several software tools for the simulation and analysis of biochemical reaction networks have been developed in the last decades; however, assessing and comparing their computational performance in executing the typical tasks of computational systems biology can be limited by the lack of a standardized benchmarking approach. …”
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Deep Neural Network Operator Acceleration Library Optimization Based on Domestic Many-core Processor by GAO Jie, LIU Sha, HUANG Ze-qiang, ZHENG Tian-yu, LIU Xin, QI Feng-bin

“…Operator acceleration libraries based on different hardware devices have become an indispensable part of deep learning framework,which can provide performance improvement for large-scale training or inference tasks dramatically.The current main-stream operator libraries are all developed based on GPU architecture,which is not compatible with other heterogeneous designs.SWDNN operator library is based on the development of SW26010 processor,which can not give full play to the performance of the upgraded SW26010 pro processor,nor can it meet the needs of the current large neural network models such as GPT-3 for large memory capacity and high memory access bandwidth.According to the architecture characteristics of SW26010 pro processor and the training requirements of large neural network model,a three-level parallel and neural network operator task sche-duling scheme based on multi-core group is proposed,which can satisfy the memory requirements of large model training and improve the overall computing performance and parallel efficiency.A memory access optimization method with triple asynchronous flow and overlap of computation and memory access is proposed,which significantly alleviates the memory access performance bottleneck of neural network operators.Based on the above methods,this paper constructs the SWTensor many-core group operator acceleration library based on the SW26010 pro processor.The experimental results of natural language processing model GPT-2 show that,computation-intensive operators and memory access intensive operators in SWTensor operator library reach the maxi-mum of 90.4% and 88.7% of the theoretical peak values respectively in single-precision floating-point computing performance and memory access bandwidth.…”
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Optimizing Resource Efficiencies for Scalable Full-Stack Quantum Computers by Marco Fellous-Asiani, Jing Hao Chai, Yvain Thonnart, Hui Khoon Ng, Robert S. Whitney, Alexia Auffèves

“…It mandates a synergy of fundamental physics and engineering: the former for the microscopic aspects of computing performance and the latter for the macroscopic resource consumption. …”
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Multivariate Singular Spectrum Analysis: A Principled, Practical, and Performant Solution for Time Series Imputation and Forecasting by Alomar, Abdullah

“…Finally, through rigorous experiments, we show that tspDB provides state-of-the-art statistical accuracy while maintaining a superior computational performance with an incremental model update, low model training time, and low latency for prediction queries.…”
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Parallel Hybrid Algorithms for a Finite Family of <i>G</i>-Nonexpansive Mappings and Its Application in a Novel Signal Recovery by Suthep Suantai, Kunrada Kankam, Watcharaporn Cholamjiak, Watcharaporn Yajai

“…Moreover, we show the computational performance of our algorithm in comparison to some methods. …”
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Robust numerical method for a singularly perturbed problem arising in the modelling of enzyme kinetics by John J. H. Miller, Eugene O'Riordan

“…Numerical results are presented to illustrate the computational performance of the numerical method. The numerical method is also remarkably simple to implement. ?…”
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Simplified likelihoods using linearized systematic uncertainties by N. Berger

“…This simplification leads to large gains in computing performance for the evaluation and maximization of the likelihood function, compared to the original statistical model. …”
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Binocular Disparity Calculation on a Massively-Parallel Analog Vision Processor by Mandal, Soumyajit, Shi, Bertram, Dudek, Piotr

“…Our goal was to make efficient use of the available hardware while preserving the fundamental computations performed by the models. We also developed an optical fixture that used mirrors to simultaneously focus two images onto the vision chip. …”
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Qualitative Knowledge, Casual Reasoning and the Localization of Failures by Brown, Allen

“…This report investigates some techinques appropriate to representing the knowledge necessary for understanding a class of electronic machines -- radio receivers. A computational performance model - WATSON - is presented. WATSONs task is to isolate failures in radio receivers whose principles of operation have been appropriately described in his knowledge base. …”
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Mapping large-scale systems on to high density FPGAs by Herath, Kalindu Bandara

“…While state-of-the-art CAD tools are capable of efficiently mapping small to medium-scale designs, they suffer from prohibitively long compilation time, higher power consumption and sub-optimal compute performance for large applications. In this thesis, novel techniques have been proposed to accelerate the mapping of large applications into high-density heterogeneous FPGAs while lowering the overall power consumption without compromising compute performance. …”
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A Low-Cost Fully Integer-Based CNN Accelerator on FPGA for Real-Time Traffic Sign Recognition by Jaemyung Kim, Jin-Ku Kang, Yongwoo Kim

“…The proposed hardware accelerator achieves a computation performance of 960 MOPS and a frame rate of 40 FPS when implemented on a Xilinx ZC706 SoC. …”
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Towards real-time fluid dynamics simulation: a data-driven NN-MPS method and its implementation by Qinghe Yao, Zhuolin Wang, Yi Zhang, Zijie Li, Junyang Jiang

“…ABSTRACTIn this work, we construct a data-driven model to address the computing performance problem of the moving particle semi-implicit method by combining the physics intuition of the method with a machine-learning algorithm. …”
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Inertial Iterative Schemes with Variable Step Sizes for Variational Inequality Problem Involving Pseudomonotone Operator by Jamilu Abubakar, Poom Kumam, Habib ur Rehman, Abdulkarim Hassan Ibrahim

“…Numerical experiments both in finite- and infinite-dimensional spaces are reported to illustrate the inertial effect and the computational performance of the proposed algorithms in comparison with the existing state of the art algorithms.…”
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A Weak Convergence Self-Adaptive Method for Solving Pseudomonotone Equilibrium Problems in a Real Hilbert Space by Pasakorn Yordsorn, Poom Kumam, Habib ur Rehman, Abdulkarim Hassan Ibrahim

“…Many numerical experiments are presented to explain the computational performance of the method and to equate them with others.…”
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Quantum Computational Supremacy by Harrow, Aram W., Montanaro, Ashley

“…A key milestone in this field will be when a universal quantum computer performs a computational task that is beyond the capability of any classical computer, an event known as quantum supremacy. …”
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Algorithm for DNA sequence assembly by quantum annealing by Katarzyna Nałęcz-Charkiewicz, Robert M. Nowak

“…Conclusions Proof of concept carried out by us showed that the use of quantum annealer (QA) for the de novo assembly task might be a promising alternative to the computations performed in the classical model. The current computing power of the available devices requires a hybrid approach (combining CPU and QPU computations). …”
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