IHPP: An In-Depth Profiling Tool for Advanced Performance Analysis
Jyoti Singh · Panamerican mathematical journal. · 2024
IHPP (In-Depth High-Precision Profiler) is a special- ized profiling tool designed to provide detailed performance analysis and insights into program execution. It addresses limitations of traditional profilers by offering intra-procedural and inter- procedural modes of analysis. The tool is implemented using Pin, a dynamic binary instrumentation framework, which allows it to add extensive instrumentation to target programs. The profiling capabilities of IHPP are categorized into various modes: funcMode: Focuses on function-level profiling, identifying call relationships and performance metrics for specific routines. intraMode: Pro- vides granular, intra-procedural profiling, analyzing the internal behavior of individual functions and algorithms. interMode: Targets interactions between different functions or procedures across the program. A key feature of IHPP is its handling of complex scenarios involving public symbols and unusual routine behaviors. The tool includes mechanisms to handle forward jumps and maintain accurate performance data even when encountering ”evil” routines. Performance metrics of IHPP reveal significant slow- down during profiling, especially with intensive instrumentation. The slowdown varies depending on the profiling mode and the complexity of the analyzed program. Despite these performance impacts, IHPP offers valuable insights that go beyond traditional profilers, particularly for algorithmic optimization and low-level analysis. The paper concludes with a discussion on the potential for future improvements, including the development of a graphical user interface and broader platform support, which would enhance the usability and applicability of IHPP. The tool represents a step forward in performance profiling, offering deeper insights into program execution for both algorithm development and optimiz