.png){kind=icon}
.png){kind=icon}
Return
Hardware support for contention tracking in CPU and GPU last-level cache
.png){kind=icon}
OA
AI
DOI：10.1016/j.sysarc.2025.103591.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Modern MPSoCs increasingly rely on resource utilization to improve application performance with different computation needs. The last-level cache (LLC) is one of the main shared resources, contributing to the improvement of aggregated performance. However, LLC sharing also increases individual application performance variability, which is undesirable in scenarios where performance guarantees are required. While deploying cache partitioning mechanisms allows regaining predictability, they negatively affect aggregated performance. This confronts system designers with the dire conundrum of choosing between aggregated performance and predictability. We contend that adding hardware support to track contention among tasks (kernels) in the LLC enables it to be shared, removing shortcomings brought by partitioning while providing a clear view of how tasks (kernels) affect each other in the LLC of the CPUs and GPUs. This approach enables achieving the desired balance between performance and predictability. Thus, we propose a low-overhead hardware mechanism, called demotion counters (DC), that tightly estimates the contention tasks (kernels) generate on each other in the shared LLC, outperforming other solutions that build on existing hardware contention-tracking proposals which suffer an average workload breakdown deviation (wbd) over 0.13. Our results also show that DC introduces 0.66% area overhead.1
Keywords:
Last Level Cache
Resource Sharing
Contention
Monitoring
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
4.1
Papers:
3.0K
Citations:
4.2K
