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CBANA: A Lightweight, Efficient, and Flexible Cache Behavior Analysis Framework

delete2024-09-01
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PRE
AI
Q
Qilin Hu
丁岩 封面图
丁岩 (Yan Ding)
刘楚波 封面图
刘楚波 (Chubo Liu) *
李克勤 封面图
李克勤 (Keqin Li)
李肯立 封面图
李肯立 (Kenli Li)
A
Albert Y. Zomaya
DOI:10.1109/TC.2024.3416747delete
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摘要

摘要

En 中文
Cache miss analysis has become one of the most important things to improve the execution performance of a program. Generally, the approaches for analyzing cache misses can be categorized into dynamic analysis and static analysis. The former collects sampling statistics during program execution but is limited to specialized hardware support and incurs expensive execution overhead. The latter avoids the limitations but faces two challenges: inaccurate execution path prediction and inefficient analysis resulted by the explosion of the program state graph. To overcome these challenges, we propose CBANA, an LLVM- and process address space-based lightweight, efficient, and flexible cache behavior analysis framework. CBANA significantly improves the prediction accuracy of the execution path with awareness of inputs. To improve analysis efficiency and utilize the program preprocessing, CBANA refactors loop structures to reduce search space and dynamically splices intermediate results to reduce unnecessary or redundant computations. CBANA also supports configurable hardware parameter settings, and decouples the module of cache replacement policy from other modules. Thus, its flexibility is established. We evaluate CBANA by using the popular open benchmark PolyBench, graph workloads, and our synthetic workloads with good and poor data locality. Compared with the popular dynamic cache analysis tools Perf and Valgrind, the cache miss gap is less than 3.79% and 2.74% respectively with over ten thousand data accesses for the synthetic workloads, and the time reduction is up to 92.38% and 97.51% for the multiple-path workloads. Compared with the popular static cache analysis tool Heptane, CBANA achieves a time reduction of 97.71% while ensuring accuracy at the same time.
Keyword:
Static analysis
Hardware
Accuracy
Performance analysis
Explosions
Analytical models
Data models
Cache behavior modeling
path analysis
path selection
static analysis

期刊

IEEE Transactions on Computers 封面图
IEEE Transactions on Computers
IF:
3.8
论文数:
5.3K
被引数:
9.8K

机构

U
University of Sydney
学者数:
6.5W
论文数: 6.2W
被引数: 90
H
hunan university
学者数:
4.5W
论文数: 3.3W
被引数: 70
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