PEAK: Cost-Adaptive Profiling in a Heartbeat
Yuheng Chen, Junjie Li, Chun‐Yaung Lu, Yinzhi Wang · 2025
Instrumentation-based profiling is essential for uncovering fine-grained optimization opportunities in High-Performance Computing (HPC) and cloud applications, yet static instrumentation methods often impose fixed profiling overheads that cannot adapt to the dynamic workloads from applications at runtime. We further develop PEAK, a Dynamic Binary Instrumentation (DBI)-based profiler with two complementary modes for overhead control: a static mode, which enforces an upper limit on the absolute instrumentation overhead, and a dynamic mode based on the heartbeat mechanism, which controls the relative overhead in real time to maintain a user-defined ratio. Evaluations of workloads ranging from compute-intensive kernels to lightweight functions show that the heartbeat mechanism effectively bounds overhead while improving profile accuracy compared to static methods, delivering predictable and adaptive profiling performance for long-running, dynamic workloads.