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plasma-umass / scalene

Scalene: a high-performance, high-precision CPU, GPU, and memory profiler for Python with AI-powered optimization proposals
Apache License 2.0
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Running scalene causes blue screen of death on Window 11 machine #422

Closed jpmorr closed 2 years ago

jpmorr commented 2 years ago

When I try to run scalene on a script, my computer immediately dies and I get a Blue Screen error from Windows. I'm running Windows 11. I've no idea what causes it.

When I try to import it into a script to focus on a specific function using from scalene import scalene_profiler it throws a error: NameError: name 'scalene_profiler' is not defined. I thought scalene should just run out of the box but I can't get it to do anything other than crash my computer.

Any help to debug this would be appreciated!

emeryberger commented 2 years ago

Insane! Are you using WSL2 or just vanilla Windows 11? What version of Python?

jpmorr commented 2 years ago

Vanilla windows 11, python 3.9.13, scalene 1.5.10.

I can try a good reference example (not my breaking script) on this machine that keeps crashing and a windows 10 or ubuntu machine if that helps?

jpmorr commented 2 years ago

I've just tried the example in the introductory video:

import numpy as np

def main():
    x = np.array(range(10**7))
    y = np.array(np.random.uniform(0, 100, size=(10**8)))

main()

Even that crashes my computer. I haven't tested on another machine, but I assume given that it won't run that code, then this is pretty machine specific.

emeryberger commented 2 years ago

I just ran the same versions of Python and Scalene on Windows 11 (admittedly, in a VM), and everything worked fine.

On the above code (python.exe -m scalene testme.py), works fine - brings up the expected web interface with the appropriate info, etc.

(I did notice that the CLI produced an odd output, which is surprising, but a lot less of a concern than crashing. Found the issue: The CLI output looks great with Windows Terminal; don't use Windows Console Host.)

Can you post the output of pip freeze?

jpmorr commented 2 years ago

pip freeze output:

aiohttp @ file:///D:/bld/aiohttp_1649013334059/work
aiosignal @ file:///home/conda/feedstock_root/build_artifacts/aiosignal_1636093929600/work
alabaster @ file:///home/ktietz/src/ci/alabaster_1611921544520/work
anaconda-client @ file:///C:/ci/anaconda-client_1635342725944/work
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anaconda-project @ file:///home/conda/feedstock_root/build_artifacts/anaconda-project_1632773999114/work
anyio @ file:///D:/bld/anyio_1652464116721/work/dist
appdirs @ file:///home/conda/feedstock_root/build_artifacts/appdirs_1603108395799/work
argh @ file:///home/conda/feedstock_root/build_artifacts/argh_1595627874344/work
argon2-cffi @ file:///home/conda/feedstock_root/build_artifacts/argon2-cffi_1640817743617/work
argon2-cffi-bindings @ file:///D:/bld/argon2-cffi-bindings_1649500515836/work
arrow @ file:///home/conda/feedstock_root/build_artifacts/arrow_1643313750486/work
asn1crypto @ file:///home/conda/feedstock_root/build_artifacts/asn1crypto_1647369152656/work
astroid @ file:///D:/bld/astroid_1652112112351/work
astropy @ file:///D:/bld/astropy_1653590270747/work
asttokens @ file:///home/conda/feedstock_root/build_artifacts/asttokens_1618968359944/work
async-generator @ file:///home/ktietz/src/ci/async_generator_1611927993394/work
async-timeout @ file:///home/conda/feedstock_root/build_artifacts/async-timeout_1640026696943/work
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attrs @ file:///home/conda/feedstock_root/build_artifacts/attrs_1640799537051/work
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awkward @ file:///D:/bld/awkward_1649793987904/work
Babel @ file:///home/conda/feedstock_root/build_artifacts/babel_1651737115240/work
backcall @ file:///home/ktietz/src/ci/backcall_1611930011877/work
backports.functools-lru-cache @ file:///tmp/build/80754af9/backports.functools_lru_cache_1618170165463/work
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bcrypt @ file:///D:/bld/bcrypt_1651441745194/work
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bitarray @ file:///D:/bld/bitarray_1652238744713/work
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icecream @ file:///home/conda/feedstock_root/build_artifacts/icecream_1644999580818/work
idna @ file:///home/conda/feedstock_root/build_artifacts/idna_1642433548627/work
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incremental @ file:///home/conda/feedstock_root/build_artifacts/incremental_1621907170877/work
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intake @ file:///home/conda/feedstock_root/build_artifacts/intake_1641785762997/work
intervaltree @ file:///Users/ktietz/demo/mc3/conda-bld/intervaltree_1630511889664/work
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ipython @ file:///D:/bld/ipython_1651240751817/work
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ipywidgets @ file:///home/conda/feedstock_root/build_artifacts/ipywidgets_1647456365981/work
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itemadapter @ file:///home/conda/feedstock_root/build_artifacts/itemadapter_1652457180940/work
itemloaders @ file:///home/conda/feedstock_root/build_artifacts/itemloaders_1605273565796/work
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keyring @ file:///D:/bld/keyring_1653312769042/work
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lazy-object-proxy @ file:///D:/bld/lazy-object-proxy_1649033324076/work
libarchive-c @ file:///D:/bld/python-libarchive-c_1649436172246/work
libmambapy @ file:///D:/bld/mamba-split_1658856160353/work/libmambapy
line-profiler @ file:///D:/bld/line_profiler_1647945098206/work
llvmlite==0.36.0
locket @ file:///home/conda/feedstock_root/build_artifacts/locket_1650660393415/work
loguru @ file:///D:/bld/loguru_1649442981921/work
lsq-ellipse==2.2.1
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lz4 @ file:///D:/bld/lz4_1652795749933/work
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Markdown @ file:///home/conda/feedstock_root/build_artifacts/markdown_1651821407140/work
MarkupSafe @ file:///D:/bld/markupsafe_1648737757460/work
matplotlib @ file:///D:/bld/matplotlib-suite_1651609646819/work
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matplotx @ file:///home/conda/feedstock_root/build_artifacts/matplotx_1652831270549/work
mccabe==0.6.1
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mistune @ file:///D:/bld/mistune_1635844891406/work
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mock @ file:///D:/bld/mock_1648992969698/work
more-itertools @ file:///home/conda/feedstock_root/build_artifacts/more-itertools_1652515549581/work
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navigator-updater==0.2.1
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nbclient @ file:///home/conda/feedstock_root/build_artifacts/nbclient_1652155694429/work
nbconvert @ file:///home/conda/feedstock_root/build_artifacts/nbconvert-meta_1649676641343/work
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networkx @ file:///home/conda/feedstock_root/build_artifacts/networkx_1653162972907/work
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nose @ file:///tmp/build/80754af9/nose_1606773131901/work
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numpydoc @ file:///home/conda/feedstock_root/build_artifacts/numpydoc_1648619272706/work
olefile @ file:///home/conda/feedstock_root/build_artifacts/olefile_1602866521163/work
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orjson==3.7.12
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pandas @ file:///D:/bld/pandas_1653497239685/work
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panel @ file:///home/conda/feedstock_root/build_artifacts/panel_1653429099596/work
param @ file:///home/conda/feedstock_root/build_artifacts/param_1648753599418/work
paramiko @ file:///home/conda/feedstock_root/build_artifacts/paramiko_1652792654356/work
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pathlib2 @ file:///D:/bld/pathlib2_1649684229157/work
pathspec @ file:///home/conda/feedstock_root/build_artifacts/pathspec_1626613672358/work
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platformdirs @ file:///home/conda/feedstock_root/build_artifacts/platformdirs_1645298319244/work
plotly @ file:///home/conda/feedstock_root/build_artifacts/plotly_1654895488764/work
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ply==3.11
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Protego @ file:///home/conda/feedstock_root/build_artifacts/protego_1647348122707/work
protobuf==3.19.4
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py @ file:///home/conda/feedstock_root/build_artifacts/py_1636301881863/work
pyarrow==8.0.0
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pycparser @ file:///home/conda/feedstock_root/build_artifacts/pycparser_1636257122734/work
pyct==0.4.6
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PyDispatcher==2.0.5
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pyflakes @ file:///home/conda/feedstock_root/build_artifacts/pyflakes_1633634815271/work
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s3transfer @ file:///home/conda/feedstock_root/build_artifacts/s3transfer_1654039987929/work
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vtk===-PKG-VERSION
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watchdog @ file:///D:/bld/watchdog_1652635556577/work
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zope.interface @ file:///D:/bld/zope.interface_1649175877560/work

Could it be hardware related? Is it trying to run on GPU? I've tried the --cpu-only but that still causes a crash. It's very weird.

emeryberger commented 2 years ago

Sounds like a possible hardware issue, and yes, it is trying to use the GPU. On Windows, --cpu-only is the only option; it really means "don't do memory / copy volume profiling", which we do not yet support on Windows. It still will try to do GPU profiling if it detects an NVIDIA GPU. There's currently no way to disable GPU profiling at the command line.

(I am thinking of changing the options to --cpu, --gpu, --memory, and --all (with the latter as the default), while deprecating the other instructions.)

However, if you are willing to get into the source code, you could clone the repository, manually disable GPU profiling by inserting a return in the constructor in scalene/scalene_gpu.py, and install from the local directory (python3 -m pip install -e .).

jpmorr commented 2 years ago

OK, if GPU details are useful let me know and I can post them. The different options sound like a great idea!

If I get a chance, I can try the workaround you suggest, but it's likely to be easier for me to find a different computer/workstation to test on!

emeryberger commented 2 years ago

Sure, please try this on another computer if you can!

jpmorr commented 2 years ago

I've tested scalene on another windows laptop without an Nvidia GPU and it seems to run fine (Although the web output neither matches that shown in the video or the newer demo example for some reason), so this points to a hardware issue with my main system. Here's the spec for reference:

OS Name:                   Microsoft Windows 11 Pro
OS Version:                10.0.22000 N/A Build 22000
OS Manufacturer:           Microsoft Corporation
OS Configuration:          Standalone Workstation
OS Build Type:             Multiprocessor Free

Processor              Intel(R) Core(TM) i9-9880H CPU @ 2.30GHz, 2304 Mhz, 8 Core(s), 16 Logical Processor(s)

Name                       NVIDIA Quadro RTX 5000
Driver Version             30.0.15.1179
Name                       Intel(R) UHD Graphics 630
Driver Version             31.0.101.2111

BIOS Version:              HP R92 Ver. 01.20.00, 23/03/2022

Total Physical Memory:     32,539 MB
Virtual Memory: Max Size:  54,043 MB

Hyper-V Requirements:      A hypervisor has been detected. Features required for Hyper-V will not be displayed.
jpmorr commented 2 years ago

So I thought the driver version looked a bit old, but it's actually windows reporting 30.0.15.1179 instead of 511.79 as Nvidia reports it, so not actually too bad. Anyway, updating the Nvidia driver to 516.94 has resolved the problem. No more instant death.