Result for 037BDD04AB7E111BFEDE19C201AFEF8218324665

Query result

Key Value
FileName./usr/share/doc/python-pycuda-doc/html/array.html
FileSize118327
MD5ADEA189ACE14EAE4A6D6C93D3ADF6D84
SHA-1037BDD04AB7E111BFEDE19C201AFEF8218324665
SHA-256F7874C23F7CA5FB31025049459C56A2D38D177837936613B9186E09AE9A818C0
SSDEEP1536:XNZGSVsUBS55tLmc0JuvQuz0FVuGPu10125P:XXGSVsUBS55tLNQuYuzyuEu1gu
TLSHT10DC36261EAD109375877A7F4D3AC1B22B2F0041BFE4008E578FD8B9B8B9BC53B516919
hashlookup:parent-total1
hashlookup:trust55

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Parents (Total: 1)

The searched file hash is included in 1 parent files which include package known and seen by metalookup. A sample is included below:

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