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Low Overhead Allocation Sampling in a Garbage Collected Virtual Machine
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DOI：10.5381/jot.2026.25.1.a16.png)
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Abstract
En 中文
Compared to the more commonly used time-based profiling, allocation profiling provides an alternate view of the execution of allocation heavy dynamically typed languages. However, profiling every single allocation in a program is very inefficient. We present a sampling allocation profiler that is deeply integrated into the garbage collector of PyPy, a Python virtual machine. This integration ensures tunable low overhead for the allocation profiler, which we measure and quantify. Enabling allocation sampling profiling with a sampling period of 4 MB leads to a maximum time overhead of 25% in our benchmarks, over un-profiled regular execution.
Keywords:
Sampling Profiler
Allocation Profiler
Python
PyPy
Garbage Collection
Journal
J
IF:
1.4
Papers:
20
Citations:
0