19 papers · ranked by Valyu relevance
Authors not listed
With the ever-increasing demand for atomistic structures representative of real-life systems as well as the ad-vent of exascale computers, it has now become necessary and possible to use advanced global optimization (GO) techniques to intelligently sample the potential energy surface (PES). Given the previous studies…
Karame Mohammadiporshokooh, Steven R. Brandt, R. Tohid, Hartmut Kaiser
'Hartmut Kaiser'] Abstract. C++ Executors simplify the development of parallel algorithms by abstracting concurrency management across hardware architectures. They are designed to facilitate portability and uniformity of user-facing interfaces; however, in some cases they may lead to performance inefficiencies due to…
Dipanwita Guhathakurta, Fatemeh Rastgar, M. Aditya Sharma, K. Madhava Krishna + 1 more
'K. Madhava Krishna' 'Arun Kumar Singh'] We present a joint multi-robot trajectory optimizer that can compute trajectories for tens of robots in aerial swarms within a small fraction of a second. The computational efficiency of our approach is built on breaking the per-iteration computation of the joint optimization…
Jesper Larsson Träff
These lecture notes are designed to accompany an imaginary, virtual, undergraduate, one or two semester course on fundamentals of Parallel Computing as well as to serve as background and reference for graduate courses on High-Performance Computing, parallel algorithms and shared-memory multiprocessor programming. They…
Ashish Chapagain, Dima Abuoliem, In Ho Cho, Tongbiao Wang
Multifunctional nanosurfaces receive growing attention due to their versatile properties. Capillary force lithography (CFL) has emerged as a simple and economical method for fabricating these surfaces. In recent works, the authors proposed to leverage the evolution strategies (ES) to modify nanosurface characteristics…
Chuan-Chi Wang, Chun‐Yen Ho, Chia-Heng Tu, Shih‐Hao Hung
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 groups are formed to calculate the information of particles and the…
Rabab Alkhalifa, Fatima Alkhomayes, Boushra Almazroua, Dana Alhaidan + 2 more
'Maryam Alothman' 'Jumana Almuhaidib'] The Traveling Salesman Problem (TSP) is a well-known NP-hard combinatorial optimization problem with wide-ranging applications in logistics, routing, and intelligent systems. Due to its factorial complexity, solving large-scale instances requires scalable and efficient algorithmic…
Bahman Arasteh, Seyed Salar Sefati, Huseyin Kusetogullari, Farzad Kiani + 3 more
Efficient task scheduling remains a key challenge in High-Performance Computing and Internet of Things (IoT) systems, where the sequential execution of nested loops often limits parallelism. This paper proposes a hybrid approach that dynamically parallelizes nested loops in heterogeneous IoT environments. The suggested…
S.E. Tavares, Carmo P. Brás, A. L. Custódio, Vítor Duarte + 1 more
'Pedro D. Medeiros'] Direct Multisearch (DMS) is a Derivative-free Optimization class of algorithms suited for computing approximations to the complete Pareto front of a given Multiobjective Optimization problem. It has a well-supported convergence analysis and simple implementations present a good numerical…
Manuel Carrer, Henrique Musseli Cezar, Sigbjørn Løland Bore, Morten Ledum + 1 more
We develop #-HylleraasMD (#-HyMD), a fully end-to-end differentiable molecular dynamics software based on the Hamiltonian hybrid particle-field formalism, and use it to establish a protocol for automated optimization of force field parameters. #-HyMD is templated on the recently established HylleraaasMD software, while…
Zuhan Liu, Kexin Zhao, Xuehu Liu, Huan Xu
With the rapid expansion of industrialization and urbanization, fine Particulate Matter (PM2.5) pollution has escalated into a major global environmental crisis. This pollution severely affects human health and ecosystem stability. Accurately predicting PM2.5 levels is essential. However, air quality forecasting…
Shuhei Watanabe, Neeratyoy Mallik, Edward M. Bergman, Frank Hutter
Zero-Cost Benchmarks Authors: ['Shuhei Watanabe' 'Neeratyoy Mallik' 'Edward M. Bergman' 'Frank Hutter'] Abstract While deep learning has celebrated many successes, its results often hinge on the meticulous selection of hyperparameters (HPs). However, the time-consuming nature of deep learning training makes HP…
Sirilak Ketchaya, Apisit Rattanatranurak
Quicksort is an important algorithm that uses the divide and conquer concept, and it can be run to solve any problem. The performance of the algorithm can be improved by implementing this algorithm in parallel. In this paper, the parallel sorting algorithm named the Multi-Deque Partition Dual-Deque Merge Sorting…
Yifan Wu, Aron Walsh, Alex Ganose
What is the minimum number of experiments, or calculations, required to find an optimal solution? Relevant chemical problems range from identifying a compound with target functionality within a given phase space to controlling materials synthesis and device fabrication conditions. A common feature in this application…
Ian Knight, Khanh Tang, John Irwin
Molecular docking is a widely used technique for leveraging protein structure in ligand discovery, but as a method, it remains difficult to utilize due to limitations that have not been adequately addressed. Despite some progress towards automation, docking still requires expert guidance, hindering its adoption by a…
Andre KY Low, Flore Mekki-Berrada, Aleksandr Ostudin, Jiaxun Xie + 7 more
The development of automated high-throughput experimental platforms has enabled fast sampling of high-dimensional decision spaces. To reach target properties efficiently, these platforms are increasingly paired with intelligent experimental design. When solving optimization problems, Bayesian-based optimizers are often…
Authors not listed
Background: Pharmaceutical batch scheduling in multi-reactor configurations presents complex optimization challenges under operational uncertainty, yet limited research addresses how parallel processing capacity affects heuristic performance and predictive modeling. Objectives: This study investigated scheduling…
Authors not listed
This study presents a novel application of Multi-Objective Bayesian Optimization (MOBO) to enhance the formulation of flame-retardant polypropylene (PP) composites. Our goal was to optimize the chemical composition of intumescent polypropylene (PP) formulations by maximizing the Limiting Oxygen Index (LOI) and…
Riley Hickman, Priyansh Parakh, Austin Cheng, Qianxiang Ai + 3 more
Experiment planning algorithms are a required component of autonomous platforms for scientific discovery. Selecting a suitable optimization algorithm for a novel application is an important yet difficult choice a researcher has to make based on past empirical performance on similar tasks. To facilitate the evaluation…