Closed
Description
[The bug here is that some BLAS libraries will crash if you pass in > 16 GiB arrays, because they use 32-bit indices internally. The most obvious solution is to break the dot call into multiple calls to dgemm, though there are also other possibilities. Original report follows:]
On python 2.7.8, numpy 1.9.1, on Mac OS X:
import numpy
numpy.random.seed(1)
X = numpy.random.random((50000,100))
numpy.dot(X, X.T)
Results in:
Segmentation fault: 11
Segfault doesn't occur on smaller arrays (e.g. 30000x100 is fine). In case it's useful, some linkage info:
>>> numpy.__config__.show()
atlas_threads_info:
NOT AVAILABLE
blas_opt_info:
extra_link_args = ['-Wl,-framework', '-Wl,Accelerate']
extra_compile_args = ['-msse3', '-DAPPLE_ACCELERATE_SGEMV_PATCH', '-I/System/Library/Frameworks/vecLib.framework/Headers']
define_macros = [('NO_ATLAS_INFO', 3)]
atlas_blas_threads_info:
NOT AVAILABLE
openblas_info:
NOT AVAILABLE
lapack_opt_info:
extra_link_args = ['-Wl,-framework', '-Wl,Accelerate']
extra_compile_args = ['-msse3', '-DAPPLE_ACCELERATE_SGEMV_PATCH']
define_macros = [('NO_ATLAS_INFO', 3)]
openblas_lapack_info:
NOT AVAILABLE
atlas_info:
NOT AVAILABLE
lapack_mkl_info:
NOT AVAILABLE
blas_mkl_info:
NOT AVAILABLE
atlas_blas_info:
NOT AVAILABLE
mkl_info:
NOT AVAILABLE
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