University of Florence
Program runtime behavior exhibits significant variations across multiple scales. The increasing design complexity and technology scaling make microprocessor performance and efficiency increasingly depend on runtime workload dynamics. Therefore understanding the effect of design parameters on workload dynamics at early, microarchitecture exploration stage is crucial for high-performance and complexity-efficient designs. In this paper, the authors apply wavelet-based analysis to decompose workload dynamics into a series of wavelet coefficients, which represent program behavior ranging from low-resolution approximation to high-resolution detail.