Result for 0527D686553356A57ED90D1E6D7D587B1BDC0B2D

Query result

Key Value
FileName./usr/share/doc/python-pycuda-doc/examples/download-examples-from-wiki.py
FileSize1706
MD55382108F62D0A94527BB45A80B0333D7
SHA-10527D686553356A57ED90D1E6D7D587B1BDC0B2D
SHA-25658FD05F356C1BB3E40A8A41C2026350BB29DCC94958574EF52D2B2A04B8930A5
SSDEEP24:N29xwHukYhCXy28ZjkwcqjKrBKoeBRuoRiXjW0fqrgtN3W2ixEEPqSp2ZV:NIOHYhCCZjkh4qBBeBRuNy0FN3WlEE3G
TLSHT11C31F27D40223414E383B698ED9690690F36D96BC3617575FFEC83968FF0A3A967021E
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