TY - GEN
T1 - Handling write backs in multi-level cache analysis for WCET estimation
AU - Zhang, Zhenkai
AU - Guo, Zhishan
AU - Koutsoukos, Xenofon
N1 - Funding Information:
This work is supported in part by the National Science Foundation (CNS-1739328), as well as a startup grant and a seed grant from Intelligent System Center at Missouri University of Science and Technology.
Publisher Copyright:
© 2017 Association for Computing Machinery.
PY - 2017/10/4
Y1 - 2017/10/4
N2 - In this paper, we investigate how to soundly analyze multi-level caches that employ write-back policy at each level for worst-case execution time (WCET) estimation. To the best of our knowledge, there is only one existing approach for dealing with write backs in multi-level cache analysis. However, as shown in the paper, this existing approach is not sound. In order to soundly handle write backs, at a cache level, we need to consider whether a memory block is potentially dirty and when such a potentially dirty block may be evicted from the cache. To this end, we introduce a dirty attribute into persistence analysis for tracking dirty blocks, and over-approximate a write back window for each possible write back. Based on the overestimated write back occurring times, we propose an approach that can soundly deal with write backs in analysis of multi-level (unifed) caches for WCET estimation. Possible write back costs are also integrated into path analysis. We evaluate the proposed approach on a set of benchmarks to demonstrate its efectiveness.
AB - In this paper, we investigate how to soundly analyze multi-level caches that employ write-back policy at each level for worst-case execution time (WCET) estimation. To the best of our knowledge, there is only one existing approach for dealing with write backs in multi-level cache analysis. However, as shown in the paper, this existing approach is not sound. In order to soundly handle write backs, at a cache level, we need to consider whether a memory block is potentially dirty and when such a potentially dirty block may be evicted from the cache. To this end, we introduce a dirty attribute into persistence analysis for tracking dirty blocks, and over-approximate a write back window for each possible write back. Based on the overestimated write back occurring times, we propose an approach that can soundly deal with write backs in analysis of multi-level (unifed) caches for WCET estimation. Possible write back costs are also integrated into path analysis. We evaluate the proposed approach on a set of benchmarks to demonstrate its efectiveness.
KW - Multi-level cache analysis
KW - WCET estimation
KW - Write back handling
UR - http://www.scopus.com/inward/record.url?scp=85037341184&partnerID=8YFLogxK
U2 - 10.1145/3139258.3139269
DO - 10.1145/3139258.3139269
M3 - Conference contribution
AN - SCOPUS:85037341184
T3 - ACM International Conference Proceeding Series
SP - 208
EP - 217
BT - Proceedings of the 25th International Conference on Real-Time Networks and Systems, RTNS 2017
PB - Association for Computing Machinery
Y2 - 4 October 2017 through 6 October 2017
ER -