Comments (7)
Hardware platform? What happens when you run nvidia-smi
? (Scalene's GPU support is currently limited to NVIDIA.)
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Hardware platform? What happens when you run
nvidia-smi
? (Scalene's GPU support is currently limited to NVIDIA.)
sorry, forgot the details:
- Intel i7-13700 with RTX 3080.
- Also tried on Jetson Orin 16GB and got same issue, but let's not focus on this.
- I will add that I tried different versions (latest from github, 1.5.19, I don't remember the rest, but I tried multiple ones in this range)
- Python version 3.8
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The usual issue here is an old driver, but let's be sure. Please run nvidia-smi
and paste the output here.
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I see
here is the output of nvidia-smi while the scalene is running
Is it a CUDA version issue?
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The driver version is a little bit on the old side (released in 2022); if you can update it to the latest version, please do and let's see what happens. In my experience, this usually resolves the problem.
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@aibtw any updates?
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Sorry, been testing it with different conditions.
So, after I updated the driver to 530,
I setup a new venv to test it.
If I run it on a non-threaded application, it seems to work
(but GPU memory result doesn't seem right to me)
However, my application is threaded. If I run it, it is still the same.
So, does it work for threaded applications?
I really like the tool. Appreciate your effort in trying to solve this.
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Related Issues (20)
- GUI Filter: Display only functions / methods with profiled lines
- Discrepency between online GUI and the generated HTML HOT 1
- Ollama server is not detected HOT 3
- Environment variables from .env file are not loaded HOT 1
- Add ability to control whether `profile.html` is generated HOT 1
- ImportError: dlopen with crdp.abi3.so, 0x0002: bad bind opcode 0x00 HOT 6
- Scalene doesnt work properly with torchrun / torch.distributed.run HOT 3
- scalene doesn't see code loaded via exec?
- Is there a way to not use GPU monitoring and pynvml? HOT 1
- Build failure on MacOS when using nix
- Filtering and exclusion by library or module HOT 2
- Scalene breaks code that accesses files on a s3 mountpoint HOT 3
- ast.parse crashes in certain edge cases HOT 4
- scalene doesn't print gpu utilization HOT 1
- Multiprocessing Pool Crash HOT 3
- Package is marked as incompatible with Python 3.11 HOT 1
- Unable to export scalene summary as a Json output HOT 1
- Pinning `setuptools` is causing build failures in nixpkgs HOT 2
- Per-thread allocation tracking
- Running pytest on Charcoal-SE/Smokedetector under scalene fails HOT 5
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