Tree-like distributed computation environment with shapp library

Tomasz Gałecki , Wiktor B. Daszczuk

Abstract

Despite the rapidly growing computing power of computers, it is often insufficient to perform mass calculations in a short time, for example, simulation of systems for various sets of parameters, the searching of huge state spaces, optimization using ant or genetic algorithms, machine learning, etc. One can solve the problem of a lack of computing power through workload management systems used in local networks in order to use the free computing power of servers and workstations. This article proposes raising such a system to a higher level of abstraction: The use in the. NET environment of a new Shapp library that allows remote task execution using fork-like operations from Portable Operating System Interface for UNIX (POSIX) systems. The library distributes the task code, sending static data on which task force is working, and individualizing tasks. In addition, a convenient way of communicating distributed tasks running hierarchically in the Shapp library was proposed to better manage the execution of these tasks. Many different task group architectures are possible; we focus on tree-like calculations that are suitable for many problems where the range of possible parallelism increases as the calculations progress.
Author Tomasz Gałecki (FEIT / ICS)
Tomasz Gałecki,,
- The Institute of Computer Science
, Wiktor B. Daszczuk (FEIT / IN)
Wiktor B. Daszczuk,,
- The Institute of Computer Science
Journal seriesInformation (Switzerland), [Information (Switzerland)], ISSN 2078-2489
Issue year2020
Vol11
Pages1-25
Publication size in sheets1.2
Article number143
Keywords in Englishworkload management; remote fork; distributed computations; task group communication
ASJC Classification1710 Information Systems
DOIDOI:10.3390/info11030143
Languageen angielski
File
Tree-Like Distributed Computation Environment with Shapp Library.pdf 962.03 KB
Score (nominal)40
Score sourcejournalList
ScoreMinisterial score = 40.0, 27-08-2020, ArticleFromJournal
Publication indicators Scopus Citations = 0; Scopus SNIP (Source Normalised Impact per Paper): 2018 = 1.034
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