Presentation
PEAK: Cost-Adaptive Profiling in a Heartbeat
DescriptionInstrumentation-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.
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.
Event Type
Workshop
TimeMonday, 17 November 20255:00pm - 5:30pm CST
Location241