A Theoretical Graph based Framework for Parameter Tuning of Multi-core Systems Article Swipe
Surendra Kumar Shukla
,
Devesh Pratap Singh
,
Shaili Gupta
,
Kireet Joshi
,
Vishan Kumar Gupta
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.5815/ijwmt.2022.04.02
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.5815/ijwmt.2022.04.02
Multi-core systems are outperforming nowadays.Therefore, various computing paradigms are intrinsically incorporated in the multicore domain to exploit its potential and solve well known computing problems.Parameter tuning is a well-known computing problem in the field of Multicore domain.Addressing the said hurdle would leverage in the performance enhancement of Multicore systems.Various efforts in this direction have been made through the conventional parameter tuning algorithms in a limited scope; however, the problem is yet not addressed completely.In this research article, we have addressed parameter tuning problem by employing applications of graph theory, especially Dijkstra shortest path algorithm to address the said issue.Dijkstra's principle has been applied to establish correlation among the parameters further tuning by finding the pair of suitable parameters.Two other algorithms which are based on application feedback (to provide performance goals to the system) has been introduced.The proposed algorithms collectively (as a framework), addressed the parameter tuning problem.The effectiveness of the algorithms is verified and further measured in distinct parameter tuning scenarios and promising outcome has been achieved.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.5815/ijwmt.2022.04.02
- http://www.mecs-press.org/ijwmt/ijwmt-v12-n4/IJWMT-V12-N4-2.pdf
- OA Status
- diamond
- Cited By
- 17
- References
- 22
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4319781079
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4319781079Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.5815/ijwmt.2022.04.02Digital Object Identifier
- Title
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A Theoretical Graph based Framework for Parameter Tuning of Multi-core SystemsWork title
- Type
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articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-08-08Full publication date if available
- Authors
-
Surendra Kumar Shukla, Devesh Pratap Singh, Shaili Gupta, Kireet Joshi, Vishan Kumar GuptaList of authors in order
- Landing page
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https://doi.org/10.5815/ijwmt.2022.04.02Publisher landing page
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https://www.mecs-press.org/ijwmt/ijwmt-v12-n4/IJWMT-V12-N4-2.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
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diamondOpen access status per OpenAlex
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https://www.mecs-press.org/ijwmt/ijwmt-v12-n4/IJWMT-V12-N4-2.pdfDirect OA link when available
- Concepts
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Core (optical fiber), Computer science, Graph, Theoretical computer science, TelecommunicationsTop concepts (fields/topics) attached by OpenAlex
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17Total citation count in OpenAlex
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2025: 3, 2024: 9, 2023: 4, 2022: 1Per-year citation counts (last 5 years)
- References (count)
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22Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.(to | 126 |
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| abstract_inverted_index.efforts | 49 |
| abstract_inverted_index.exploit | 16 |
| abstract_inverted_index.finding | 112 |
| abstract_inverted_index.further | 109, 154 |
| abstract_inverted_index.limited | 64 |
| abstract_inverted_index.outcome | 163 |
| abstract_inverted_index.problem | 30, 68, 82 |
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| abstract_inverted_index.Dijkstra | 90 |
| abstract_inverted_index.article, | 76 |
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| abstract_inverted_index.feedback | 125 |
| abstract_inverted_index.however, | 66 |
| abstract_inverted_index.leverage | 41 |
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| abstract_inverted_index.research | 75 |
| abstract_inverted_index.shortest | 91 |
| abstract_inverted_index.suitable | 116 |
| abstract_inverted_index.verified | 152 |
| abstract_inverted_index.Multicore | 35, 47 |
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| abstract_inverted_index.addressed | 72, 79, 142 |
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| abstract_inverted_index.computing | 6, 23, 29 |
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| abstract_inverted_index.employing | 84 |
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| abstract_inverted_index.principle | 99 |
| abstract_inverted_index.promising | 162 |
| abstract_inverted_index.scenarios | 160 |
| abstract_inverted_index.Multi-core | 0 |
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| abstract_inverted_index.enhancement | 45 |
| abstract_inverted_index.framework), | 141 |
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| abstract_inverted_index.completely.In | 73 |
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