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Low Overhead Allocation Sampling in a Garbage Collected Virtual Machine Christoph Jung, C. F. Bolz-Tereick https://arxiv.org/abs/2506.16883 https://arxiv.org/pdf/2506.16883 https://arxiv.org/html/2506.16883 arXiv:2506.16883v1 Announce Type: new Abstract: 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. toXiv_bot_toot