Factors for Search Methods Scalability

Research output: Chapter in Book/Report/Published conference proceedingChapter

Abstract

Scalability of systems performance becomes a challenge for modern digital systems. Achievement of system ability to complete wide range of tasks in terms of computational performance and effective use of resources require substantial research. Significant efforts are directed towards design of large scale hardware systems. However resolving scalable tasks require also scalable software capable of completion both many small simple tasks and large complex tasks using effectively available hardware, energy and time. This article discusses factors for successful search and optimisation in particular search methods scalability. Discussion is illustrated with an overview of publications.
Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Subtitle of host publicationNumerical Methods and Applications. NMA 2018
EditorsGeno Nikolov, Natalia Kolkovska, Krassimir Georgiev
Place of PublicationCham, Switzerlang
PublisherSpringer Nature
Pages142-149
Number of pages8
Volume11189
Edition1
ISBN (Electronic)978-3-030-10692-8
ISBN (Print)978-3-030-10691-1
DOIs
Publication statusPublished - 18 Jan 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11189 LNCS

Fingerprint

Search Methods
Scalability
Hardware
Completion
System Performance
Resources
Software
Optimization
Energy
Range of data

Cite this

Penev, K. (2019). Factors for Search Methods Scalability. In G. Nikolov, N. Kolkovska, & K. Georgiev (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Numerical Methods and Applications. NMA 2018 (1 ed., Vol. 11189, pp. 142-149). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11189 LNCS). Cham, Switzerlang: Springer Nature. https://doi.org/10.1007/978-3-030-10692-8_16
Penev, Kalin. / Factors for Search Methods Scalability. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Numerical Methods and Applications. NMA 2018. editor / Geno Nikolov ; Natalia Kolkovska ; Krassimir Georgiev. Vol. 11189 1. ed. Cham, Switzerlang : Springer Nature, 2019. pp. 142-149 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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Penev, K 2019, Factors for Search Methods Scalability. in G Nikolov, N Kolkovska & K Georgiev (eds), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Numerical Methods and Applications. NMA 2018. 1 edn, vol. 11189, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11189 LNCS, Springer Nature, Cham, Switzerlang, pp. 142-149. https://doi.org/10.1007/978-3-030-10692-8_16

Factors for Search Methods Scalability. / Penev, Kalin.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Numerical Methods and Applications. NMA 2018. ed. / Geno Nikolov; Natalia Kolkovska; Krassimir Georgiev. Vol. 11189 1. ed. Cham, Switzerlang : Springer Nature, 2019. p. 142-149 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11189 LNCS).

Research output: Chapter in Book/Report/Published conference proceedingChapter

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Penev K. Factors for Search Methods Scalability. In Nikolov G, Kolkovska N, Georgiev K, editors, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Numerical Methods and Applications. NMA 2018. 1 ed. Vol. 11189. Cham, Switzerlang: Springer Nature. 2019. p. 142-149. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-030-10692-8_16