Result for 0AF7A21ADA9C862859385813168B57B949B27175

Query result

Key Value
FileName./usr/share/doc/python-pycuda-doc/html/_sources/tutorial.txt
FileSize6921
MD55944D3B6976F3FED54F369B91AD950E8
SHA-10AF7A21ADA9C862859385813168B57B949B27175
SHA-2565189ABC2FB9B3E6C5D84B9E22BF19C0CC708CACF13A061AB4199A7E00EB62C16
SSDEEP192:+AUyWa6zcLQgJuMLxafW41LUnDHMGofRZSGp:+CWp4QOuMLKH1LUDHMGofWk
TLSHT1E6E1930E1E2977B61692E050CA4E4487E3F9C166136C9CE8746F01354B1963BA3FEBDE
hashlookup:parent-total2
hashlookup:trust60

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Parents (Total: 2)

The searched file hash is included in 2 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
FileSize119956
MD523CDA4ED64E49A236DB26EEFFAC2B1FA
PackageDescriptionmodule to access Nvidia‘s CUDA computation API (documentation) PyCUDA lets you access Nvidia‘s CUDA parallel computation API from Python. Several wrappers of the CUDA API already exist–so what’s so special about PyCUDA? * Object cleanup tied to lifetime of objects. This idiom, often called RAII in C++, makes it much easier to write correct, leak- and crash-free code. PyCUDA knows about dependencies, too, so (for example) it won’t detach from a context before all memory allocated in it is also freed. * Convenience. Abstractions like pycuda.driver.SourceModule and pycuda.gpuarray.GPUArray make CUDA programming even more convenient than with Nvidia’s C-based runtime. * Completeness. PyCUDA puts the full power of CUDA’s driver API at your disposal, if you wish. * Automatic Error Checking. All CUDA errors are automatically translated into Python exceptions. * Speed. PyCUDA’s base layer is written in C++, so all the niceties above are virtually free. * Helpful Documentation. . This package contains HTML documentation and example scripts.
PackageMaintainerUbuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageNamepython-pycuda-doc
PackageSectioncontrib/doc
PackageVersion2013.1.1+git20140310-1ubuntu1
SHA-17C32F16E8D9F9B42EE7B8391513C4F4133317A55
SHA-256F1E5743A8D81E47F415F60B257194F92B88E1D694117431EC5A9A6268AB3783C
Key Value
FileSize121238
MD5C4E65F38C34CDFB41E9E87C44B27A227
PackageDescriptionmodule to access Nvidia‘s CUDA computation API (documentation) PyCUDA lets you access Nvidia‘s CUDA parallel computation API from Python. Several wrappers of the CUDA API already exist–so what’s so special about PyCUDA? * Object cleanup tied to lifetime of objects. This idiom, often called RAII in C++, makes it much easier to write correct, leak- and crash-free code. PyCUDA knows about dependencies, too, so (for example) it won’t detach from a context before all memory allocated in it is also freed. * Convenience. Abstractions like pycuda.driver.SourceModule and pycuda.gpuarray.GPUArray make CUDA programming even more convenient than with Nvidia’s C-based runtime. * Completeness. PyCUDA puts the full power of CUDA’s driver API at your disposal, if you wish. * Automatic Error Checking. All CUDA errors are automatically translated into Python exceptions. * Speed. PyCUDA’s base layer is written in C++, so all the niceties above are virtually free. * Helpful Documentation. . This package contains HTML documentation and example scripts.
PackageMaintainerTomasz Rybak <tomasz.rybak@post.pl>
PackageNamepython-pycuda-doc
PackageSectioncontrib/doc
PackageVersion2014.1-3
SHA-11BDB201A404831B25FF18CC3D1A3D1D96C30A4CA
SHA-256D22CCAA27B9C7C511F994AE05367E43D665EB7F35F8084FA6E7BFB6A05621D04