11 papers · ranked by Valyu relevance
Cheng Ye, Bryan Thornlow, Angie Hinrichs, Devika Torvi + 3 more
Phylogenetic tree optimization is necessary for precise analysis of evolutionary and transmission dynamics, but existing tools are inadequate for handling the scale and pace of data produced during the COVID-19 pandemic. One transformative approach, online phylogenetics, aims to incrementally add samples to an…
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…
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…
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…
David R. Penas, Meysam Hashemi, Viktor K. Jirsa, Julio R. Banga
The Virtual Epileptic Patient (VEP) refers to a computer-based representation of a patient with epilepsy that combines personalized anatomical data with dynamical models of abnormal brain activities. It is capable of generating spatio-temporal seizure patterns that resemble those recorded with invasive methods such as…
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…
Máté Mohácsi, Márk Patrik Török, Sára Sáray, Luca Tar + 1 more
Finding optimal parameters for detailed neuronal models is a ubiquitous challenge in neuroscientific research. Recently, manual model tuning has been replaced by automated parameter search using a variety of different tools and methods. However, using most of these software tools and choosing the most appropriate…
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…
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…
Kecong Tang, Ahsan Sanaullah, Degui Zhi, Shaojie Zhang
Durbin’s positional Burrows-Wheeler transform (PBWT) enables algorithms with the optimal time complexity of O(MN) for reporting all vs all haplotype matches in a population panel with M haplotypes and N variant sites. However, even this efficiency may still be too slow when the number of haplotypes reaches millions. To…
Changin Oh, Kathleen P. Wilkie
We present the Toroidal Search Algorithm (TSA), a novel population-based metaheuristic optimization method inspired by the topology of a torus. Conventional metaheuristics frequently suffer from boundary stagnation, a phenomenon that severely degrades performance in bounded and high-dimensional search spaces. TSA…