An Optimized Nature-Inspired Metaheuristic Algorithm for Application Mapping in 2D-NoC.

Saleha Sikandar, Naveed Khan Baloch, Fawad Hussain, Waqar Amin, Yousaf Bin Zikria, Heejung Yu

Abstract read

In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Saleha SikandarComputer Engineering Department, University of Engineering and Technology, Taxila 47050, Pakistan.ORCID 0000-0001-7270-6035

Naveed Khan BalochComputer Engineering Department, University of Engineering and Technology, Taxila 47050, Pakistan.

Fawad HussainComputer Engineering Department, University of Engineering and Technology, Taxila 47050, Pakistan.ORCID 0000-0002-7819-5990

Waqar AminComputer Engineering Department, University of Engineering and Technology, Taxila 47050, Pakistan.

Yousaf Bin ZikriaDepartment of Information and Communication Engineering, Yeungnam University, Gyeongsan 38541, Korea.ORCID 0000-0002-6570-5306

Heejung YuDepartment of Electronics and Information Engineering, Korea University, Sejong 30019, Korea.ORCID 0000-0001-8046-2376

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mapping application task graphs on intellectual property (IP) cores into network-on-chip (NoC) is a non-deterministic polynomial-time hard problem. The evolution of network performance mainly depends on an effective and efficient mapping technique and the optimization of performance and cost metrics. These metrics mainly include power, reliability, area, thermal distribution and delay. A state-of-the-art mapping technique for NoC is introduced with the name of sailfish optimization algorithm (SFOA). The proposed algorithm minimizes the power dissipation of NoC via an empirical base applying a shared

Indexed as

metaheuristic optimizationnetwork-on-chipsailfish hunting

Identifiers

PMID34372337

DOI10.3390/s21155102

PMCPMC8347139

What OpenQuestion holds

Textmetadata

LicenceCC BY

Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.