Result for 0567F1CA0F8F03418B683AB8EC6B90B1FD98431A

Query result

Key Value
FileName./usr/lib/python3/dist-packages/pycuda/cuda/pycuda-helpers.hpp
FileSize10070
MD54C8D1D1BEBC1478587E87CAAB270CD6D
SHA-10567F1CA0F8F03418B683AB8EC6B90B1FD98431A
SHA-256DE0698D5369F896587A451FE8E05ACE2DF22530F60C9C8B09B733A12F086BE0A
SSDEEP192:v9N3RKRSlDRr6RRUzI1pZT0Ij6CD2zMrZBw2gnBr4BEWpKYPm:xwwkO
TLSHT19422F33C51AA7C0B6A63C27B9B9A0805DFA6C3D144C6FA3664DC66341D4D2CD99EC8F3
tar:gnameroot
tar:unameroot
hashlookup:parent-total32
hashlookup:trust100

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Parents (Total: 32)

The searched file hash is included in 32 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
FileSize358152
MD5C3825CF1F0AEDC95033009FB7B94B79D
PackageDescriptionPython 3 module to access Nvidia‘s CUDA parallel computation API 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 Python 3 modules.
PackageMaintainerDebian NVIDIA Maintainers <pkg-nvidia-devel@lists.alioth.debian.org>
PackageNamepython3-pycuda
PackageSectioncontrib/python
PackageVersion2021.1~dfsg-3
SHA-112B61B011445E8184C46C2B00A7EE21E1BCE300D
SHA-256DA26AF59EF98CC358ABE81F9B664005E4685AD4ECBD5F68B1121CF8C92CD3329
Key Value
FileSize314760
MD57BF0E78717DA26E6338F7BD64DFF900B
PackageDescriptionPython 3 module to access Nvidia‘s CUDA parallel computation API 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 Python 3 modules.
PackageMaintainerDebian NVIDIA Maintainers <pkg-nvidia-devel@lists.alioth.debian.org>
PackageNamepython3-pycuda
PackageSectioncontrib/python
PackageVersion2018.1.1-3
SHA-1194237D7D664B504399F5E9BEB56DA0152F10DE1
SHA-2560FEACB25B38F54A02704784F4224BB36C6531EEC2F66E69507FBA85570A04353
Key Value
FileSize466804
MD5DA783AD042E8BC1B24DD7F017C98259F
PackageDescriptionPython 3 module to access Nvidia‘s CUDA parallel computation API 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 Python 3 modules.
PackageMaintainerDebian NVIDIA Maintainers <pkg-nvidia-devel@lists.alioth.debian.org>
PackageNamepython3-pycuda
PackageSectioncontrib/python
PackageVersion2018.1.1-4+b1
SHA-1216F72108B66361221097E375E4CD57619E47A32
SHA-2567A9AE4FC9D93F552529DD8A9DA555A4C27DAC0151B8581BE57D7E041E349A221
Key Value
FileSize315996
MD59DAD2B920C5F38AE16418FC825678E96
PackageDescriptionPython 3 module to access Nvidia‘s CUDA parallel computation API 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 Python 3 modules.
PackageMaintainerDebian NVIDIA Maintainers <pkg-nvidia-devel@lists.alioth.debian.org>
PackageNamepython3-pycuda
PackageSectioncontrib/python
PackageVersion2018.1.1-3+b1
SHA-12412174B9D481D80C4933275CF9CBD46E43E7B01
SHA-25660FF2DA05EC2E8335D75BECDCFC5995F3A6FBAA1B7CE00713F30312582B9A4E4
Key Value
FileSize315604
MD56D7EDAD4A85900295C8656C15C55898B
PackageDescriptionPython module to access Nvidia‘s CUDA parallel computation API 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.
PackageMaintainerDebian NVIDIA Maintainers <pkg-nvidia-devel@lists.alioth.debian.org>
PackageNamepython-pycuda
PackageSectioncontrib/python
PackageVersion2018.1.1-3
SHA-14EF4ADCC6E4220EFE21307798BDCFF45E7722ABD
SHA-256A84B96264AAFE4114348062D6CA1C01661D2B1C3079FA0EBFD6981F3A0794D5A
Key Value
MD5BA6ED9E2057F04E33B7203B93019EE5A
PackageArchx86_64
PackageDescriptionPyCUDA lets you access NVIDIA's CUDA parallel computation API from Python 3.
PackageMaintainerdaviddavid <daviddavid>
PackageNamepython3-pycuda
PackageRelease2.mga7.nonfree
PackageVersion2018.1.1
SHA-1514707E56A9270BFCE760C39DEDB47B5DDBBA4A9
SHA-256FF83A7F9CDD3C11E94B62A7E8657B497D1181F7C4C4201B9BE53E3E2C3122A99
Key Value
MD524A50AC218C6D868AEA50CE43DC85755
PackageArchx86_64
PackageDescriptionPyCUDA lets you access NVIDIA's CUDA parallel computation API from Python 3.
PackageMaintainerwally <wally>
PackageNamepython3-pycuda
PackageRelease7.mga8.nonfree
PackageVersion2019.1.2
SHA-15AD469F0EB4A115315A610C8B8E461D0D340F3CA
SHA-2560F5936855090EA7EFFAA70C80127B3BE578896F254929658D3ED970F1E179FBC
Key Value
FileSize319636
MD512B0F72FA0DD4D4F5917C93FDDB849FD
PackageDescriptionPython 3 module to access Nvidia‘s CUDA parallel computation API 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 Python 3 modules.
PackageMaintainerUbuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageNamepython3-pycuda
PackageSectioncontrib/python
PackageVersion2018.1.1-4build3
SHA-15B6B1750FCBE9A57B1F6EB243119376976F12806
SHA-256825FD1875E492CEDCD406277A8604BECFE0D7918A2B860445F76084BF5F6DD38
Key Value
FileSize324516
MD5243CCEF4C9E154C6A489BFBE0BD7DE2F
PackageDescriptionPython 3 module to access Nvidia‘s CUDA parallel computation API 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 Python 3 modules.
PackageMaintainerDebian NVIDIA Maintainers <pkg-nvidia-devel@lists.alioth.debian.org>
PackageNamepython3-pycuda
PackageSectioncontrib/python
PackageVersion2018.1.1-4+b3
SHA-15CB7C1DC9306BF10D8A8AB8F486876259448B62A
SHA-2563FBC78D464995A76A71EA5F6B5E4A9E8B74BA4F3FBCA33B29236C8520C78A1F2
Key Value
FileSize365912
MD5F1996CF668237BB6A9C352FEF1D96F4A
PackageDescriptionPython 3 module to access Nvidia‘s CUDA parallel computation API 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 Python 3 modules.
PackageMaintainerDebian NVIDIA Maintainers <pkg-nvidia-devel@lists.alioth.debian.org>
PackageNamepython3-pycuda
PackageSectioncontrib/python
PackageVersion2021.1~dfsg-2
SHA-15CCBA9F4C5A56AD9B78B3791A34A5F26B5C917BE
SHA-256651F1600425FF7485C70FCC8287486DCE510891F1FE293E71BA326689A6C6352