Details

Autor(en) / Beteiligte

• Song, Shixin
• Khan, Tanvir Ahmed
• Shahri, Sara Mahdizadeh
• Sriraman, Akshitha
• Soundararajan, Niranjan K
• Subramoney, Sreenivas
• Jiménez, Daniel A.
• Litz, Heiner
• Kasikci, Baris

Titel

Thermometer: profile-guided btb replacement for data center applications

Ist Teil von

• Proceedings of the 49th Annual International Symposium on Computer Architecture, 2022, p.742-756

Ort / Verlag

New York, NY, USA: ACM

Erscheinungsjahr

2022

Quelle

ACM Digital Library Complete

Beschreibungen/Notizen

• Modern processors employ a decoupled frontend with Fetch Directed Instruction Prefetching (FDIP) to avoid frontend stalls in data center applications. However, the large branch footprint of data center applications precipitates frequent Branch Target Buffer (BTB) misses that prohibit FDIP from eliminating more than 40% of all frontend stalls. We find that the state-of-the-art BTB optimization techniques (e.g., BTB prefetching and replacement mechanisms) cannot eliminate these misses due to their inadequate understanding of branch reuse behavior in data center applications. In this paper, we first perform a comprehensive characterization of the branch behavior of data center applications, and determine that identifying optimal BTB replacement decisions requires considering both transient and holistic (i.e., across the entire execution) branch behavior. We then present Thermometer, a novel BTB replacement technique that realizes the holistic branch behavior via a profile-guided analysis. Based on the collected profile, Thermometer generates useful BTB replacement hints that the underlying hardware can leverage. We evaluate Thermometer using 13 widely-used data center applications and demonstrate that it provides an average speedup of 8.7% (0.4%-64.9%) while outperforming the state-of-the-art BTB replacement techniques by 5.6× (on average, the best performing prior work achieves 1.5% speedup). We also demonstrate that Thermometer achieves a performance speedup that is, on average, 83.6% of the speedup achieved by the optimal BTB replacement policy.