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Top 3 cpu-profiling Open-Source Projects
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scalene
Scalene: a high-performance, high-precision CPU, GPU, and memory profiler for Python with AI-powered optimization proposals
I collected a list of profilers (also memory profilers, also specifically for Python) here: https://github.com/albertz/wiki/blob/master/profiling.md
Currently I actually need a Python memory profiler, because I want to figure out whether there is some memory leak in my application (PyTorch based training script), and where exactly (in this case, it's not a problem of GPU memory, but CPU memory).
I tried Scalene (https://github.com/plasma-umass/scalene), which seems to be powerful, but somehow the output it gives me is not useful at all? It doesn't really give me a flamegraph, or a list of the top lines with memory allocations, but instead it gives me a listing of all source code lines, and prints some (very sparse) information on each line. So I need to search through that listing now by hand to find the spots? Maybe I just don't know how to use it properly.
I tried Memray, but first ran into an issue (https://github.com/bloomberg/memray/issues/212), but after using some workaround, it worked now. I get a flamegraph out, but it doesn't really seem accurate? After a while, there don't seem to be any new memory allocations at all anymore, and I don't quite trust that this is correct.
There is also Austin (https://github.com/P403n1x87/austin), which I also wanted to try (have not yet).
Somehow this experience so far was very disappointing.
(Side node, I debugged some very strange memory allocation behavior of Python before, where all local variables were kept around after an exception, even though I made sure there is no reference anymore to the exception object, to the traceback, etc, and I even called frame.clear() for all frames to really clear it. It turns out, frame.f_locals will create another copy of all the local variables, and the exception object and all the locals in the other frame still stay alive until you access frame.f_locals again. At that point, it will sync the f_locals again with the real (fast) locals, and then it can finally free everything. It was quite annoying to find the source of this problem and to find workarounds for it. https://github.com/python/cpython/issues/113939)
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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RISC-V-Guide
RISC-V Guide. Learn all about the RISC-V computer architecture along with the Development Tools and Operating Systems to develop on RISC-V hardware.
cpu-profiling related posts
- Hotspot: A GUI for the Linux perf profiler
- Hotspot: A GUI for the Linux perf profiler
- Scalene: A high-performance CPU GPU and memory profiler for Python
- Scalene: A high-performance, CPU, GPU, and memory profiler for Python
- How can I find out why my python is so slow?
- Cum as putea sa imbunatatesc timpul de rulare al pitonului?
- Scalene - A Python CPU/GPU/memory profiler with optimization proposals
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Index
What are some of the best open-source cpu-profiling projects? This list will help you:
Project | Stars | |
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1 | scalene | 11,125 |
2 | hotspot | 3,840 |
3 | RISC-V-Guide | 448 |