Cluster Based Adaptive Multi-Voltage Scaling Dynamic Task Mapping for WNoC and HWNoC

Cluster Based Adaptive Multi-Voltage Scaling Dynamic Task Mapping for WNoC and HWNoC | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Cluster Based Adaptive Multi-Voltage Scaling Dynamic Task Mapping for WNoC and HWNoC Rivu Ghosh, Sneha Agarwal, Mitali Sinha, Sujay Deb This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4432670/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 27 You are reading this latest preprint version Abstract Wireless Network-on-Chip (WNoC) and Hybrid Wireless Network-on-Chip (HWNoC) architectures are promising solutions for future high-performance computing systems. However, WNoC consumes significant power, while HWNoC experiences congestion over the wireless link. Several state-of-the-art task mapping algorithms have been proposed to reduce power consumption and congestion over wireless links. However, these existing task mapping algorithms face challenges related to hotspots creation, sub-optimal utilization of wireless links, and also overlook idle core power reduction strategy. Additionally, each of the existing task mapping algorithms is designed for a specific architecture, either WNoC or HWNoC. To address these challenges we propose a novel task mapping algorithm called Cluster-Based Adaptive Multi-Voltage Scaling (CB-AMS). This algorithm dynamically maps tasks to clusters while performing multi-voltage scaling based on workload to significantly reduce power consumption and congestion over wireless links. A new cluster selection strategy is also proposed in CB-AMS to address the hotspot creation issue. CB-AMS is designed to be used in both WNoC and HWNoC architecture. Experimental results show that CB-AMS significantly reduces power consumption by 41% for WNoC and by 15-20% for HWNoC compared to state-of-the-art task mapping algorithms. Experimental results also validate that CB-AMS achieves better congestion control in HWNoC architecture by reducing latency by 3.6-5.5% compared to existing task mapping algorithms. Our experimental analysis has demonstrated that CB-AMS outperforms the current algorithms and delivers significant power reduction and improved congestion control for both WNoC and HWNoC architectures. Wireless Network-on-Chip Hybrid Wireless-Network-on-Chip Task Graph Task Mapping. Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 06 Oct, 2024 Reviews received at journal 08 Sep, 2024 Reviews received at journal 26 Jun, 2024 Reviews received at journal 25 Jun, 2024 Reviews received at journal 25 Jun, 2024 Reviews received at journal 25 Jun, 2024 Reviews received at journal 18 Jun, 2024 Reviews received at journal 18 Jun, 2024 Reviews received at journal 15 Jun, 2024 Reviewers agreed at journal 10 Jun, 2024 Reviewers agreed at journal 06 Jun, 2024 Reviewers agreed at journal 02 Jun, 2024 Reviewers agreed at journal 30 May, 2024 Reviewers agreed at journal 30 May, 2024 Reviewers agreed at journal 29 May, 2024 Reviewers agreed at journal 29 May, 2024 Reviewers agreed at journal 29 May, 2024 Reviewers agreed at journal 28 May, 2024 Reviewers agreed at journal 28 May, 2024 Reviewers agreed at journal 28 May, 2024 Reviewers agreed at journal 28 May, 2024 Reviewers agreed at journal 28 May, 2024 Reviewers agreed at journal 28 May, 2024 Reviewers invited by journal 28 May, 2024 Editor assigned by journal 24 May, 2024 Submission checks completed at journal 23 May, 2024 First submitted to journal 16 May, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4432670","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":309660000,"identity":"14f58bbd-9834-4f8c-99cc-d5ef27f7b103","order_by":0,"name":"Rivu Ghosh","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAuklEQVRIiWNgGAWjYDACZhBRIcHDxsBgAGLyEKnlDFALG9FaQICxDUhAtRAG5u08ZpJf51nI8Mk3b2D4UcMgY05Ii8xhHjNp2W0gh7EVMPYcY+CxbCCgRYKZLU1aEqyFx4CBt4GBx+AAUVrmQLQw/iVOC/MxyY8NEC3MRNrCfNia4RhIS1rBYRkgg7AW/oONN3/U1NnLNx/e+PBNjY09QS0gwAyLPqBiCSLUAwHjD+LUjYJRMApGwUgFAGkxK5VSiSLnAAAAAElFTkSuQmCC","orcid":"","institution":"Indraprastha Institute of Information Technology Delhi","correspondingAuthor":true,"prefix":"","firstName":"Rivu","middleName":"","lastName":"Ghosh","suffix":""},{"id":309660001,"identity":"0142708f-bc09-402e-8dfe-816f6ec79190","order_by":1,"name":"Sneha Agarwal","email":"","orcid":"","institution":"Indraprastha Institute of Information Technology Delhi","correspondingAuthor":false,"prefix":"","firstName":"Sneha","middleName":"","lastName":"Agarwal","suffix":""},{"id":309660002,"identity":"ac0644a8-35ce-4f1a-9f45-b4cf25bb1f45","order_by":2,"name":"Mitali Sinha","email":"","orcid":"","institution":"Shell (India)","correspondingAuthor":false,"prefix":"","firstName":"Mitali","middleName":"","lastName":"Sinha","suffix":""},{"id":309660003,"identity":"96a2a003-fd5d-4d8e-8e7d-b421d106d4fb","order_by":3,"name":"Sujay Deb","email":"","orcid":"","institution":"Indraprastha Institute of Information Technology Delhi","correspondingAuthor":false,"prefix":"","firstName":"Sujay","middleName":"","lastName":"Deb","suffix":""}],"badges":[],"createdAt":"2024-05-16 17:55:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4432670/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4432670/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":57738138,"identity":"5b54bf7f-08b8-4da4-b4f0-47b67ff90ef4","added_by":"auto","created_at":"2024-06-05 02:51:45","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1498374,"visible":true,"origin":"","legend":"","description":"","filename":"ClusterBasedAdaptiveMultiVoltageScalingDynamicTaskMappingforWNoCandHWNoCSJ2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4432670/v1_covered_d1f046d8-0c3b-4d48-98bc-1e90a50009db.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Cluster Based Adaptive Multi-Voltage Scaling Dynamic Task Mapping for WNoC and HWNoC","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"the-journal-of-supercomputing","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [The Journal of Supercomputing](https://www.springer.com/journal/11227)","snPcode":"11227","submissionUrl":"https://submission.nature.com/new-submission/11227/3","title":"The Journal of Supercomputing","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Wireless Network-on-Chip, Hybrid Wireless-Network-on-Chip, Task Graph, Task Mapping.","lastPublishedDoi":"10.21203/rs.3.rs-4432670/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4432670/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eWireless Network-on-Chip (WNoC) and Hybrid Wireless Network-on-Chip (HWNoC) architectures are promising solutions for future high-performance computing systems. 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