Result for 2E8CDAD39FEF002240132D31A150CC32F2D58360

Query result

Key Value
FileName./usr/share/doc/python-pycuda-doc/examples/test_driver.py
FileSize33535
MD531A92FE1DE9C1578B41941779E6BAF81
SHA-12E8CDAD39FEF002240132D31A150CC32F2D58360
SHA-2569862189F748C8113CA995DBA6014E64F85150F2631954FA08E9A90865226E7FA
SSDEEP768:P33xk6N7McRk7JSXPxsUvOabceUbO4cbpRb5l/Vvb1PCtYA+KjIQ1Hbn/K+IjIpe:PjNwcG7oXJ1moDvPAFZbdgmurLV
TLSHT1C2E29555D57745981F1BC879ADC6421222A3B1770E8CAC94F1ECE2D08F0827AABF46FD
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
FileSize120088
MD553A701A0F851A6F96A9E6ECC8CA4B4C2
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
PackageVersion2018.1.1-4build3
SHA-165236A04197BFDC3B509FC9CF2C58757BE9FC533
SHA-256E6EC468E83B8376907BCE551B24F63862CFEB40C0175C68288B141F1245D865D
Key Value
FileSize125184
MD508962F72F9F22A4E82373D2B7C72C32B
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
PackageVersion2018.1.1-3
SHA-1AE932020CC541F9AC73BDE13723772C56864CDA2
SHA-2568B7A6937CC1B4A0C3829FF235ACDA7FBDEAE2673A25EAB80B1706D8BAB5877CA
Key Value
FileSize119808
MD58610CB0C9A5A484B4BEA977BDB93242A
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
PackageVersion2018.1.1-4build2
SHA-180020ED7FA39EC61C4C8E536392338201BA9CDBA
SHA-25666EBCDE4AB472A2C51AC159F4152B0E1243BB7C87A409F868AC6EB5414590EA8