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dc.contributor.authorSingh, Sawan-
dc.contributor.authorPerais, Arthur-
dc.contributor.authorJimborean, Alexandra-
dc.contributor.authorRos Bardisa, Alberto-
dc.date.accessioned2024-12-18T11:05:45Z-
dc.date.available2024-12-18T11:05:45Z-
dc.date.issued2024-08-01-
dc.identifier.isbn979-8-3503-2658-1-
dc.identifier.urihttp://hdl.handle.net/10201/147624-
dc.description© 2024 IEEE. This document is the Submitted version of a Published Work that appeared in final form in ACM/IEEE 51st Annual International Symposium on Computer Architecture (ISCA). To access the final edited and published work see https://doi.org/10.1109/ISCA59077.2024.00092es
dc.description.abstractDatacenter applications are well-known for their large code footprints. This has caused frontend design to evolve by implementing decoupled fetching and large prediction structures – branch predictors, Branch Target Buffers (BTBs) – to mitigate the stagnating size of the instruction cache by prefetching instructions well in advance. In addition, many designs feature a micro operation (µ-op) cache, which primarily provides power savings by bypassing the instruction cache and decoders once warmed up. However, this µ-op cache often has lower reach than the instruction cache, and it is not filled up speculatively using the decoupled fetcher. As a result, the µ-op cache is often over-subscribed by datacenter applications, up to the point of becoming a burden. This paper first shows that because of this pressure, blindly prefetching into the µ-op cache using state-of-the-art standalone prefetchers would not provide significant gains. As a consequence, this paper proposes to prefetch only critical µ-ops into the µop cache, by focusing on execution points where the µ-op cache provides the most gains: Pipeline refills. Concretely, we use hardto-predict conditional branches as indicators that a pipeline refill is likely to happen in the near future, and prefetch into the µ-op cache the µ-ops that belong to the path opposed to the predicted path, which we call alternate path. Identifying hard-to-predict branches requires no additional state if the branch predictor confidence is used to classify branches. Including extra alternate branch predictors with limited budget (8.95KB to 12.95KB), our proposal provides average speedups of 1.9% to 2% and as high as 12% on a subset of CVP-1 traces.es
dc.formatapplication/pdfes
dc.format.extent16es
dc.languageenges
dc.publisherIEEE Computer Societyes
dc.relationThis work was supported by the European Research Council under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 819134), the MCIN/AEI/10.13039/501100011033/ and the “ERDF A way of making Europe”, EU (grant PID2022-136315OB-I00), the MCIN/AEI/10.13039/501100011033/ and the European Union NextGenerationEU/PRTR (grant TED2021-130233B-C33), the European Union’s Horizon 2021 research and innovation program (grant agreement No 101070374 under HORIZONCL4-2021-DIGITAL-EMERGING-01) and the Ramon y Cajal ´ Research Contract (RYC2018-025200-I).es
dc.relation.ispartofACM/IEEE 51st Annual International Symposium on Computer Architecture (ISCA), 2024, June 29 to July 3, Buenos Aries, pp. 1230-1245es
dc.rightsinfo:eu-repo/semantics/embargoedAccesses
dc.subjectMicro op cache-
dc.subjectProcessor front end-
dc.subjectCore design-
dc.subjectPrefetching-
dc.subjectHard to predict branches-
dc.titleAlternate path µ-op cache prefetchinges
dc.typeinfo:eu-repo/semantics/articlees
dc.relation.publisherversionhttps://www.computer.org/csdl/proceedings-article/isca/2024/265800b230/1Z3pApnH41Wes
dc.embargo.termsSI-
dc.identifier.doihttps://doi.org/10.1109/ISCA59077.2024.00092-
dc.contributor.departmentDepartamento de Ingeniería y Tecnología de Computadores-
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