Result for 2B7F4C315C401E8648495F7B3A76EB2FFA746199

Query result

Key Value
FileName./usr/share/doc/python-pycuda-doc/html/objects.inv
FileSize5138
MD52936471624AE5981440EF6282A89081B
SHA-12B7F4C315C401E8648495F7B3A76EB2FFA746199
SHA-2565BB3605ABB34125AD0A3278A453FD3B20A608B7797779B274AE632B7CC8EF0B9
SSDEEP96:Tg+lrDTkd1sNmfkV6O7FBcmpi5b6Eg5wjvh5MqYn7g+ukNDYSouDnF2V/vcvft/r:drDAd1sEk6O7nRsl6Edvhhes+rDnF2VQ
TLSHT1CAB19EBC3AA3CC785E3D9665BE3D10BEB1F98408E17E89D3D255E7784148B2A0BC0910
hashlookup:parent-total3
hashlookup:trust65

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Parents (Total: 3)

The searched file hash is included in 3 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
FileSize119872
MD5E1BE81A04920A2CCC19D39426D23EAAA
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
PackageVersion2020.1~dfsg1-1
SHA-1D9EFEAA5B100FB1FE16DAC17E95FA8B4800C338C
SHA-25627AABC6F3CAEB25C9EEF55153340B0A59046ACE751C1F5FBC6B2FD1723FFA938
Key Value
FileSize121664
MD55EFE49327F7B41893841B7AF02F75F66
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.
PackageMaintainerDebian NVIDIA Maintainers <pkg-nvidia-devel@lists.alioth.debian.org>
PackageNamepython-pycuda-doc
PackageSectioncontrib/doc
PackageVersion2020.1~dfsg1-1
SHA-120A83F606344926C660B842A6C1BE23C771A9596
SHA-2568781434BDA773A0141FC847C193083B20167249F0E33E2D0A0ED6A414C424FC1
Key Value
FileSize125736
MD515DD889D5C91BC9DC291505272A59AB7
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
PackageVersion2020.1~dfsg1-1build1
SHA-1732A8163CFC4FE53D7B0C7F3B658A7B2A7AB8469
SHA-256815E02DAFD1B560DD7686BE68CC34EE72E051442886DC29AF7BE51FA1BBA2F76