Beyond Time-Quantum: A Basic-Block FDA Approach for Accurate System Computing Performance Estimation

Performance estimation is an essential technique in computer system design and optimization. Traditional time-quantum-based methods have limitations in accurately capturing program behavior due to the granularity issue. In this paper, we propose a novel approach, called Basic-Block-based Frequency Domain Analysis (BBFDA), that uses basic block analysis to extract program execution phase information and applies recursive frequency domain analysis to estimate performance waveforms. We evaluate our proposed approach on SPEC CPU2017 benchmark suites and compare it with time-quantum-based methods. Results show that our approach achieves higher accuracy and robustness than traditional methods, especially for cases with many phases. Our proposed approach can dynamically track performance behavior without the need to choose an appropriate granularity size.