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testMagneticLensPythonInterface fails #350

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afedynitch opened this issue Jul 9, 2021 · 3 comments · Fixed by #352
Closed

testMagneticLensPythonInterface fails #350

afedynitch opened this issue Jul 9, 2021 · 3 comments · Fixed by #352

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@afedynitch
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Hi!

When building latest master or 3.1.7 tag on Ubuntu 20.04 one of the tests fails with SEGFAULT.

Running tests...
Test project /home/afedyni/CRPropa3/build
Start 1: testCore
1/20 Test #1: testCore .......................... Passed 0.04 sec
Start 2: testVector3
2/20 Test #2: testVector3 ....................... Passed 0.00 sec
Start 3: testModuleList
3/20 Test #3: testModuleList .................... Passed 0.03 sec
Start 4: testMagneticField
4/20 Test #4: testMagneticField ................. Passed 0.03 sec
Start 5: testTurbulentField
5/20 Test #5: testTurbulentField ................ Passed 0.23 sec
Start 6: testAdvectionField
6/20 Test #6: testAdvectionField ................ Passed 0.03 sec
Start 7: testDensity
7/20 Test #7: testDensity ....................... Passed 0.03 sec
Start 8: testDINT
8/20 Test #8: testDINT .......................... Passed 0.05 sec
Start 9: testPropagation
9/20 Test #9: testPropagation ................... Passed 0.03 sec
Start 10: testBreakCondition
10/20 Test #10: testBreakCondition ................ Passed 0.03 sec
Start 11: testInteraction
11/20 Test #11: testInteraction ................... Passed 38.33 sec
Start 12: testSource
12/20 Test #12: testSource ........................ Passed 0.20 sec
Start 13: testOutput
13/20 Test #13: testOutput ........................ Passed 0.04 sec
Start 14: testFunctionalGroups
14/20 Test #14: testFunctionalGroups .............. Passed 0.03 sec
Start 15: testAdiabaticCooling
15/20 Test #15: testAdiabaticCooling .............. Passed 0.03 sec
Start 16: testGalacticMagneticLens
16/20 Test #16: testGalacticMagneticLens .......... Passed 0.07 sec
Start 17: testMagneticLensPythonInterface
17/20 Test #17: testMagneticLensPythonInterface ...***Exception: SegFault 0.21 sec
Start 18: testSimulationExecution
18/20 Test #18: testSimulationExecution ........... Passed 2.53 sec
Start 19: testDiffusionSDE
19/20 Test #19: testDiffusionSDE .................. Passed 3.15 sec
Start 20: testPythonExtension
20/20 Test #20: testPythonExtension ............... Passed 0.17 sec

95% tests passed, 1 tests failed out of 20

Total Test time (real) = 45.24 sec

The following tests FAILED:
17 - testMagneticLensPythonInterface (SEGFAULT)

We have tested this on different installations of Ubuntu 20.04, SWIG3 or 4, numpy 1.19.2 and 1.20.1, conda python and system python only, etc. If that's of any importance, numpy is linked to MKL 2020.0 due to other parts of our code requiring linear algebra performance on AMD Zen, we can not use openblas or other BLAS.

The SEGFAULT is triggered by the first access using numpy arrays:

def testAddParticlesNumpyInterface(self):
        try:
            import numpy as np
        except:
            print("Cannot import numpy. Not testing testAddParticlesNumpyInterface!")
            return


        N = 13
        ids = np.ones(N, dtype='i')
        lats = np.random.rand(N) * np.pi - np.pi/2.
        lons = np.random.rand(N) * np.pi * 2. - np.pi
        energy = 10 ** (18 + np.random.rand(N) * 3.) * crpropa.eV
        weights = np.ones(N) / N
        self.maps.addParticles(ids, energy, lons, lats, weights ) <----

Note that this is different from #316 where all python tests failed. Here I the library was checked with ldd what it links to and it doesn't matter if it's conda stuff or native system packages.

Thanks!

@lukasmerten
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I can reproduce this error on Ubuntu 18.

If someone encounters this problem in their analysis: you can work around this bug by manually adding particles with addParticle one at a time.

@afedynitch
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Thanks

@tdwiser
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tdwiser commented Jul 14, 2021

I also encountered this is attempting to fix #316. I'm not 100% sure what the actual issue was but fixing the segfaults involved invoking the Python Global Interpreter Lock, and also being extra careful with the memory ordering of the numpy arrays since we are messing with them manually. Skipping these steps makes the code very context sensitive to what numpy/python decide to do with your memory range when calling out to their APIs. See my hacky modifications here: tdwiser@33631c8

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3 participants