Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/71492

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dc.contributor.authorHuang, Lanpor
dc.contributor.authorLi, Da-Linpor
dc.contributor.authorWang, Kang-Pingpor
dc.contributor.authorGao, Tengpor
dc.contributor.authorTavares, Adrianopor
dc.date.accessioned2021-04-09T12:54:26Z-
dc.date.issued2020-05-
dc.identifier.issn1000-9000-
dc.identifier.urihttps://hdl.handle.net/1822/71492-
dc.description.abstractField-programmable gate arrays (FPGAs) have recently evolved as a valuable component of the heterogeneous computing. The register transfer level (RTL) design flows demand the designers to be experienced in hardware, resulting in a possible failure of time-to-market. High-level synthesis (HLS) permits designers to work at a higher level of abstraction through synthesizing high-level language programs to RTL descriptions. This provides a promising approach to solve these problems. However, the performance of HLS tools still has limitations. For example, designers remain exposed to various aspects of hardware design, development cycles are still time consuming, and the quality of results (QoR) of HLS tools is far behind that of RTL flows. In this paper, we survey the literature published since 2014 focusing on the performance optimization of HLS tools. Compared with previous work, we extend the scope of the performance of HLS tools, and present a set of three-level evaluation criteria, covering from ease of use of the HLS tools to promotion on specific metrics of QoR. We also propose performance evaluation equations for describing the relation between the performance optimization and the QoR. We find that it needs more efforts on the ease of use for efficient HLS tools. We suggest that it is better to draw an analogy between the HLS development process and the embedded system design process, and to provide more elastic HLS methodology which integrates FPGAs virtual machines.por
dc.description.sponsorshipThis work was supported by the National Natural Science Foundation of China under Grant No. 61772227, the Development Project of Jilin Province of China under Grant Nos. 20190201273JC and 2020C003, Guangdong Key Project for Applied Fundamental Research under Grant No. 2018KZDXM076, and Jilin Provincial Key Laboratory of Big Date Intelligent Computing under Grant No. 20180622002JC.por
dc.language.isoengpor
dc.publisherSpringerpor
dc.rightsrestrictedAccesspor
dc.subjectEvaluation criterionpor
dc.subjectField-programmable gate array (FPGA)por
dc.subjectHigh-level synthesis (HLS)por
dc.subjectPerformance optimizationpor
dc.subjectQuality of results (QoR)por
dc.titleA survey on performance optimization of high-level synthesis toolspor
dc.typearticlepor
dc.peerreviewedyespor
dc.relation.publisherversionhttps://link.springer.com/article/10.1007/s11390-020-9414-8por
oaire.citationStartPage697por
oaire.citationEndPage720por
oaire.citationIssue3por
oaire.citationVolume35por
dc.date.updated2021-04-08T16:51:36Z-
dc.identifier.eissn1860-4749-
dc.identifier.doi10.1007/s11390-020-9414-8por
dc.date.embargo10000-01-01-
dc.subject.wosScience & Technology-
sdum.export.identifier10443-
sdum.journalJournal of Computer Science and Technologypor
Aparece nas coleções:CAlg - Artigos em revistas internacionais / Papers in international journals

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