TY - GEN
T1 - BiRFIA
T2 - 37th ACM International Conference on Supercomputing, ICS 2023
AU - Lei, Kelun
AU - You, Xin
AU - Yang, Hailong
AU - Luan, Zhongzhi
AU - Qian, Depei
N1 - Publisher Copyright:
© 2023 ACM.
PY - 2023/6/21
Y1 - 2023/6/21
N2 - Function interception of fully-optimized binaries is widely used for optimization with its ability to accurately collect runtime information and detect inefficiencies at the function level. However, the implementation of function interception with existing binary rewriting techniques still suffers from limited reliability and performance on ARM platform. In this paper, we propose BiRFIA, an efficient selective binary rewriting framework for function interception targeting highly optimized binaries on ARM platforms. BiRFIA performs static binary rewriting of specific functions and intercepts them through well-formed trampoline sections and external instrumentation libraries. Besides, BiRFIA places complex instrumentation code in the trampoline section and jumps to the trampoline section via an adaptive instruction eviction strategy, which significantly reduces the probability of unexpected errors. For evaluation, we develop two function interception tools based on BiRFIA, including a function performance event counter collector and a function parameter tracer. Guided by these tools, we optimize several benchmarks and real-world programs, yielding up to 8% performance speedup. Our evaluation result demonstrates that BiRFIA incurs negligible runtime overhead of 1.006× on average.
AB - Function interception of fully-optimized binaries is widely used for optimization with its ability to accurately collect runtime information and detect inefficiencies at the function level. However, the implementation of function interception with existing binary rewriting techniques still suffers from limited reliability and performance on ARM platform. In this paper, we propose BiRFIA, an efficient selective binary rewriting framework for function interception targeting highly optimized binaries on ARM platforms. BiRFIA performs static binary rewriting of specific functions and intercepts them through well-formed trampoline sections and external instrumentation libraries. Besides, BiRFIA places complex instrumentation code in the trampoline section and jumps to the trampoline section via an adaptive instruction eviction strategy, which significantly reduces the probability of unexpected errors. For evaluation, we develop two function interception tools based on BiRFIA, including a function performance event counter collector and a function parameter tracer. Guided by these tools, we optimize several benchmarks and real-world programs, yielding up to 8% performance speedup. Our evaluation result demonstrates that BiRFIA incurs negligible runtime overhead of 1.006× on average.
KW - ARM
KW - function interception
KW - selective binary rewriting
UR - https://www.scopus.com/pages/publications/85168414046
U2 - 10.1145/3577193.3593701
DO - 10.1145/3577193.3593701
M3 - 会议稿件
AN - SCOPUS:85168414046
T3 - Proceedings of the International Conference on Supercomputing
SP - 87
EP - 98
BT - ACM ICS 2023 - Proceedings of the International Conference on Supercomputing
PB - Association for Computing Machinery
Y2 - 21 June 2023 through 23 June 2023
ER -