Matches in SemOpenAlex for { <https://semopenalex.org/work/W3107652887> ?p ?o ?g. }
Showing items 1 to 81 of
81
with 100 items per page.
- W3107652887 abstract "High-level synthesis (HLS) raises the level of design abstraction, expedites the process of hardware design, and enriches the set of final designs by automatically translating a behavioral specification into a hardware implementation. To obtain different implementations, HLS users can apply a variety of knobs, such as loop unrolling or function inlining, to particular code regions of the specification. The applied knob configuration significantly affects the synthesized design's performance and cost, e.g., application latency and area utilization. Hence, HLS users face the design-space exploration (DSE) problem, i.e. determine which knob configurations result in Pareto-optimal implementations in this multi-objective space. Whereas it can be costly in time and resources to run HLS flows with an enormous number of knob configurations, machine learning approaches can be employed to predict the performance and cost. Still, they require a sufficient number of sample HLS runs. To enhance the training performance and reduce the sample complexity, we propose a transfer learning approach that reuses the knowledge obtained from previously explored design spaces in exploring a new target design space. We develop a novel neural network model for mixed-sharing multi-domain transfer learning. Experimental results demonstrate that the proposed model outperforms both single-domain and hard-sharing models in predicting the performance and cost at early stages of HLS-driven DSE." @default.
- W3107652887 created "2020-12-07" @default.
- W3107652887 creator A5009992367 @default.
- W3107652887 creator A5091778993 @default.
- W3107652887 date "2020-11-16" @default.
- W3107652887 modified "2023-10-16" @default.
- W3107652887 title "Transfer Learning for Design-Space Exploration with High-Level Synthesis" @default.
- W3107652887 cites W1995341919 @default.
- W3107652887 cites W2094998159 @default.
- W3107652887 cites W2108242004 @default.
- W3107652887 cites W2138209363 @default.
- W3107652887 cites W2140669431 @default.
- W3107652887 cites W2165698076 @default.
- W3107652887 cites W2398354748 @default.
- W3107652887 cites W2615755298 @default.
- W3107652887 cites W2774970068 @default.
- W3107652887 cites W2887280559 @default.
- W3107652887 cites W2900129920 @default.
- W3107652887 cites W2911122160 @default.
- W3107652887 cites W3013057549 @default.
- W3107652887 cites W3146803896 @default.
- W3107652887 doi "https://doi.org/10.1145/3380446.3430636" @default.
- W3107652887 hasPublicationYear "2020" @default.
- W3107652887 type Work @default.
- W3107652887 sameAs 3107652887 @default.
- W3107652887 citedByCount "21" @default.
- W3107652887 countsByYear W31076528872021 @default.
- W3107652887 countsByYear W31076528872022 @default.
- W3107652887 countsByYear W31076528872023 @default.
- W3107652887 crossrefType "proceedings-article" @default.
- W3107652887 hasAuthorship W3107652887A5009992367 @default.
- W3107652887 hasAuthorship W3107652887A5091778993 @default.
- W3107652887 hasConcept C111472728 @default.
- W3107652887 hasConcept C113775141 @default.
- W3107652887 hasConcept C118524514 @default.
- W3107652887 hasConcept C124304363 @default.
- W3107652887 hasConcept C138885662 @default.
- W3107652887 hasConcept C149635348 @default.
- W3107652887 hasConcept C169590947 @default.
- W3107652887 hasConcept C199360897 @default.
- W3107652887 hasConcept C26713055 @default.
- W3107652887 hasConcept C2776221188 @default.
- W3107652887 hasConcept C41008148 @default.
- W3107652887 hasConcept C42935608 @default.
- W3107652887 hasConcept C58013763 @default.
- W3107652887 hasConcept C76155785 @default.
- W3107652887 hasConcept C76970557 @default.
- W3107652887 hasConcept C82876162 @default.
- W3107652887 hasConceptScore W3107652887C111472728 @default.
- W3107652887 hasConceptScore W3107652887C113775141 @default.
- W3107652887 hasConceptScore W3107652887C118524514 @default.
- W3107652887 hasConceptScore W3107652887C124304363 @default.
- W3107652887 hasConceptScore W3107652887C138885662 @default.
- W3107652887 hasConceptScore W3107652887C149635348 @default.
- W3107652887 hasConceptScore W3107652887C169590947 @default.
- W3107652887 hasConceptScore W3107652887C199360897 @default.
- W3107652887 hasConceptScore W3107652887C26713055 @default.
- W3107652887 hasConceptScore W3107652887C2776221188 @default.
- W3107652887 hasConceptScore W3107652887C41008148 @default.
- W3107652887 hasConceptScore W3107652887C42935608 @default.
- W3107652887 hasConceptScore W3107652887C58013763 @default.
- W3107652887 hasConceptScore W3107652887C76155785 @default.
- W3107652887 hasConceptScore W3107652887C76970557 @default.
- W3107652887 hasConceptScore W3107652887C82876162 @default.
- W3107652887 hasLocation W31076528871 @default.
- W3107652887 hasOpenAccess W3107652887 @default.
- W3107652887 hasPrimaryLocation W31076528871 @default.
- W3107652887 hasRelatedWork W1732210391 @default.
- W3107652887 hasRelatedWork W2017506008 @default.
- W3107652887 hasRelatedWork W2056509023 @default.
- W3107652887 hasRelatedWork W2057648092 @default.
- W3107652887 hasRelatedWork W2130097981 @default.
- W3107652887 hasRelatedWork W2140882033 @default.
- W3107652887 hasRelatedWork W2547383453 @default.
- W3107652887 hasRelatedWork W2787803743 @default.
- W3107652887 hasRelatedWork W2904693267 @default.
- W3107652887 hasRelatedWork W3147787617 @default.
- W3107652887 isParatext "false" @default.
- W3107652887 isRetracted "false" @default.
- W3107652887 magId "3107652887" @default.
- W3107652887 workType "article" @default.