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The performance of biomolecular molecular dynamics simulations has steadily increased on modern high performance computing resources but acceleration of the analysis of the output trajectories has lagged behind so that analyzing simulations…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-03-31 Mahzad Khoshlessan , Ioannis Paraskevakos , Geoffrey C. Fox , Shantenu Jha , Oliver Beckstein

We compare automatically and manually parallelized NAS Benchmarks in order to identify code sections that differ. We discuss opportunities for advancing automatic parallelizers. We find ten patterns that pose challenges for current…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-12-02 Parinaz Barakhshan , Rudolf Eigenmann

Priority queues with parallel access are an attractive data structure for applications like prioritized online scheduling, discrete event simulation, or greedy algorithms. However, a classical priority queue constitutes a severe bottleneck…

Data Structures and Algorithms · Computer Science 2021-07-23 Marvin Williams , Peter Sanders , Roman Dementiev

In this paper, we present several improvements in the parallelization of the in-place merge algorithm, which merges two contiguous sorted arrays into one with an O(T) space complexity (where T is the number of threads). The approach divides…

Distributed, Parallel, and Cluster Computing · Computer Science 2020-05-27 Berenger Bramas , Quentin Bramas

Multi-Robot Path Planning (MRPP) on graphs, equivalently known as Multi-Agent Path Finding (MAPF), is a well-established NP-hard problem with critically important applications. As serial computation in (near)-optimally solving MRPP…

Robotics · Computer Science 2024-03-19 Teng Guo , Jingjin Yu

Traditional public blockchain systems typically had very limited transaction throughput because of the bottleneck of the consensus protocol itself. With recent advances in consensus technology, the performance limit has been greatly lifted,…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-02-11 Péter Garamvölgyi , Yuxi Liu , Dong Zhou , Fan Long , Ming Wu

Extract-Transform-Load (ETL) handles large amount of data and manages workload through dataflows. ETL dataflows are widely regarded as complex and expensive operations in terms of time and system resources. In order to minimize the time and…

Databases · Computer Science 2014-09-08 Xiufeng Liu

The rapid rise in demand for training large neural network architectures has brought into focus the need for partitioning strategies, for example by using data, model, or pipeline parallelism. Implementing these methods is increasingly…

A typical enterprise uses a local area network of computers to perform its business. During the off-working hours, the computational capacities of these networked computers are underused or unused. In order to utilize this computational…

Distributed, Parallel, and Cluster Computing · Computer Science 2009-08-21 Que Thu Dung Nguyen

Parallel algorithms designed for simulation and performance evaluation of single-server tandem queueing systems with both infinite and finite buffers are presented. The algorithms exploit a simple computational procedure based on recursive…

Numerical Analysis · Mathematics 2012-11-30 Sergei M. Ermakov , Nikolai K. Krivulin

A large fraction of an XML document typically consists of text data. The XPath query language allows text search via the equal, contains, and starts-with predicates. Such predicates can efficiently be implemented using a compressed…

Databases · Computer Science 2011-10-06 A. Arroyuelo , F. Claude , S. Maneth , V. Mäkinen , G. Navarro , K. Nguyen , J. Siren , N. Välimäki

Extending Bayesian optimization to batch evaluation can enable the designer to make the most use of parallel computing technology. However, most of current batch approaches do not scale well with the batch size. That is, their performances…

Machine Learning · Computer Science 2025-04-25 Dawei Zhan , Zhaoxi Zeng , Shuoxiao Wei , Ping Wu

We report on an experimental investigation into opportunities for parallelism in beliefnet inference. Specifically, we report on a study performed of the available parallelism, on hypercube style machines, of a set of randomly generated…

Artificial Intelligence · Computer Science 2013-03-25 Bruce D'Ambrosio , Tony Fountain , Zhaoyu Li

In this work I present a generalization of Amdahl's law on the limits of a parallel implementation with many processors. In particular I establish some mathematical relations involving the number of processors and the dimension of the…

Distributed, Parallel, and Cluster Computing · Computer Science 2007-05-23 Gianluca Argentini

This paper proposes a general formulation for temporal parallelisation of dynamic programming for optimal control problems. We derive the elements and associative operators to be able to use parallel scans to solve these problems with…

Optimization and Control · Mathematics 2022-01-25 Simo Särkkä , Ángel F. García-Fernández

As the artificial intelligence community advances into the era of large models with billions of parameters, distributed training and inference have become essential. While various parallelism strategies-data, model, sequence, and…

Machine Learning · Computer Science 2025-03-13 Ruifeng She , Bowen Pang , Kai Li , Zehua Liu , Tao Zhong

In this paper I describe some results on the use of virtual processors technology for parallelize some SPMD computational programs. The tested technology is the INTEL Hyper Threading on real processors, and the programs are MATLAB scripts…

Distributed, Parallel, and Cluster Computing · Computer Science 2007-05-23 Gianluca Argentini

Recently, research communities highlight the necessity of formulating a scalability continuum for large-scale graph processing, which gains the scale-out benefits from distributed graph systems, and the scale-up benefits from…

Distributed, Parallel, and Cluster Computing · Computer Science 2022-04-01 Kai Zou , Xike Xie , Qi Li , Deyu Kong

This paper presents a multiagent approach as a paradigm for scheduling parallel jobs in a parallel system. Scheduling parallel jobs is performed as a means to balance the load of a system in order to improve the performance of a parallel…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-06-29 Jaderick P. Pabico

Nowadays, several industrial applications are being ported to parallel architectures. These applications take advantage of the potential parallelism provided by multiple core processors. Many-core processors, especially the GPUs(Graphics…

Distributed, Parallel, and Cluster Computing · Computer Science 2011-03-28 Wendell Rodrigues , Frédéric Guyomarc'h , Jean-Luc Dekeyser