Implementation of the Tagged Geometric History Length Access Interval Predictor

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in KonferenzbandBeigetragenBegutachtung

Beitragende

Abstract

Sharing tightly coupled memories (TCMs) is popular in embedded multi-processor systems-on-a-chip (MPSoCs) to improve hardware efficiency and software flexibility. The obligatory access conflict resolution logic may be detrimental to the system’s critical path and therefore the performance. Access interval prediction (AIP) mitigates this degradation by enabling offline arbitration. A couple of AIP algorithms have been presented, some reaching accuracies of over $97 \%$. This paper presents the first register-transfer level (RTL) implementation of one of these—the tagged geometric history length access interval predictor (TAGE-AIP). We present two predictor variants, one with a clock frequency of 600 MHz and an accuracy of $97.1 \%$ and a smaller reduced variant running at 625 MHz with 96.9 % accuracy. The prediction and update procedures fit in the given time budget in both variants. We analyze the area and the timing of the design and how it is influenced by the design parameters.

Details

OriginalspracheEnglisch
Titel2024 IEEE Nordic Circuits and Systems Conference (NorCAS)
Redakteure/-innenJari Nurmi, Joachim Rodrigues, Luca Pezzarossa, Viktor Aberg, Baktash Behmanesh
Herausgeber (Verlag)Institute of Electrical and Electronics Engineers (IEEE)
Seitenumfang4
ISBN (elektronisch)979-8-3315-1766-3
ISBN (Print)979-8-3315-1767-0
PublikationsstatusVeröffentlicht - 30 Okt. 2024
Peer-Review-StatusJa

Konferenz

Titel2024 IEEE Nordic Circuits and Systems Conference
KurztitelNorCAS 2024
Dauer29 - 30 Oktober 2024
Webseite
BekanntheitsgradInternationale Veranstaltung
OrtStadshall Lund
StadtLund
LandSchweden

Externe IDs

Scopus 85211931312

Schlagworte

Schlagwörter

  • Accuracy, Clocks, History, Memory management, Pipeline processing, Prediction algorithms, Software, Software algorithms, Timing, Tuning, MPSoC, access interval, Memory prediction, shared memory