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Productivity of a low-budget computer cluster applied to overcome the n-body problem

Nowicki Tomasz, Gregosiewicz Adam, Łagodowski Zbigniew

Applied Computer Science

2021

Vol. 17, no 4

100--109

The classical n-body problem in physics addresses the prediction of individual motions of a group of celestial bodies under gravitational forces and has been studied since Isaac Newton formulated his laws. Nowadays the n-body problem has been recognized in many more fields of science and engineering. Each problem of mutual interaction between objects forming a dynamic group is called as the n-body problem. The cost of the direct algorithm for the problem is O(n2) and is not acceptable from the practical point of view. For this reason cheaper algorithms have been developed successfully reducing the cost to O(nln(n)) or even O(n). Because further improvement of the algorithms is unlikely to happen it is the hardware solutions which can still accelerate the calculations. The obvious answer here is a computer cluster that can preform the calculations in parallel. This paper focuses on the performance of a low-budget computer cluster created on ad hoc basis applied to n-body problem calculation. In order to maintain engineering valuable results a real technical issue was selected to study. It was Discrete Vortex Method that is used for simulating air flows. The pre-sented research included writing original computer code, building a computer cluster, preforming simulations and comparing the results.

A Hybrid CPU/GPU Cluster for Encryption and Decryption of Large Amounts of Data

Niewiadomska-Szynkiewicz E., Marks M., Jantura J., Podbielski M.

Journal of Telecommunications and Information Technology

2012

nr 3

32-39

The main advantage of a distributed computing system over standalone computer is an ability to share the workload between cores, processors and computers. In our paper we present a hybrid cluster system - a novel computing architecture with multi-core CPUs working together with many-core GPUs. It integrates two types of CPU, i.e., Intel and AMD processor with advanced graphics processing units, adequately, Nvidia Tesla and AMD FirePro (formerly ATI). Our CPU/GPU cluster is dedicated to perform massive parallel computations which is a common approach in cryptanalysis and cryptography. The efficiency of parallel implementations of selected data encryption and decryption algorithms are presented to illustrate the performance of our system.