Improved Converted Traces from Rebasing Microarchitectural Research with Industry Traces

  1. Feliu, Josué 1
  2. Perais, Arthur 2
  3. Jiménez, Daniel A. 3
  4. Ros, Alberto 4
  1. 1 Universidad Politécnica de Valencia
    info

    Universidad Politécnica de Valencia

    Valencia, España

    ROR https://ror.org/01460j859

  2. 2 Univ. Grenoble Alpes, CNRS, Grenoble INP, TIMA
  3. 3 Texas A&M University
    info

    Texas A&M University

    College Station, Estados Unidos

    ROR https://ror.org/01f5ytq51

  4. 4 Universidad de Murcia
    info

    Universidad de Murcia

    Murcia, España

    ROR https://ror.org/03p3aeb86

Éditeur: Zenodo

Année de publication: 2023

Type: Dataset

CC BY 4.0

Résumé

Improved converted traces of the paper "Rebasing Microarchitectural Research with Industry Traces", published at the 2023 IEEE International Symposium on Workload Characterization. It includes the CVP-1 traces used in the paper converted with our improved converter. Abstract: Microarchitecture research relies on performance models with various degrees of accuracy and speed. In the past few years, one such model, ChampSim, has started to gain significant traction by coupling ease of use with a reasonable level of detail and simulation speed. At the same time, datacenter class workloads, which are not trivial to set up and benchmark, have become easier to study via the release of hundreds of industry traces following the first Championship Value Prediction (CVP-1) in 2018. A tool was quickly created to port the CVP-1 traces to the ChampSim format, which, as a result, have been used in many recent works. We revisit this conversion tool and find that several key aspects of the CVP-1 traces are not preserved by the conversion. We therefore propose an improved converter that addresses most conversion issues as well as patches known limitations of the CVP-1 traces themselves. We evaluate the impact of our changes on two commits of ChampSim, with one used for the first Instruction Championship Prefetching (IPC-1) in 2020. We find that the performance variation stemming from higher accuracy conversion is significant.

Références bibliographiques

  • 10.1109/IISWC59245.2023.00027