Parents (Total: 16)

The searched file hash is included in 16 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
FileSize	6590628
MD5	60A7AD4F424B1DAB98A345B927477AFB
PackageDescription	Python 3 module to access Nvidia‘s CUDA API (debug extensions) 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 debug extensions for the Python 3 debug interpreter.
PackageMaintainer	Debian NVIDIA Maintainers <pkg-nvidia-devel@lists.alioth.debian.org>
PackageName	python3-pycuda-dbg
PackageSection	contrib/debug
PackageVersion	2018.1.1-4+b3
SHA-1	1C5C4B522EB7C0C34DE03A3C22FB63789912072A
SHA-256	00D672EADDFA9F08764ED994BF52A7F15459D417D8BBA09AE1766132B0569292

Key	Value
FileSize	466804
MD5	DA783AD042E8BC1B24DD7F017C98259F
PackageDescription	Python 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.
PackageMaintainer	Debian NVIDIA Maintainers <pkg-nvidia-devel@lists.alioth.debian.org>
PackageName	python3-pycuda
PackageSection	contrib/python
PackageVersion	2018.1.1-4+b1
SHA-1	216F72108B66361221097E375E4CD57619E47A32
SHA-256	7A9AE4FC9D93F552529DD8A9DA555A4C27DAC0151B8581BE57D7E041E349A221

Key	Value
FileSize	319636
MD5	12B0F72FA0DD4D4F5917C93FDDB849FD
PackageDescription	Python 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.
PackageMaintainer	Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageName	python3-pycuda
PackageSection	contrib/python
PackageVersion	2018.1.1-4build3
SHA-1	5B6B1750FCBE9A57B1F6EB243119376976F12806
SHA-256	825FD1875E492CEDCD406277A8604BECFE0D7918A2B860445F76084BF5F6DD38

Key	Value
FileSize	324516
MD5	243CCEF4C9E154C6A489BFBE0BD7DE2F
PackageDescription	Python 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.
PackageMaintainer	Debian NVIDIA Maintainers <pkg-nvidia-devel@lists.alioth.debian.org>
PackageName	python3-pycuda
PackageSection	contrib/python
PackageVersion	2018.1.1-4+b3
SHA-1	5CB7C1DC9306BF10D8A8AB8F486876259448B62A
SHA-256	3FBC78D464995A76A71EA5F6B5E4A9E8B74BA4F3FBCA33B29236C8520C78A1F2

Key	Value
FileSize	120088
MD5	53A701A0F851A6F96A9E6ECC8CA4B4C2
PackageDescription	module 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.
PackageMaintainer	Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageName	python-pycuda-doc
PackageSection	contrib/doc
PackageVersion	2018.1.1-4build3
SHA-1	65236A04197BFDC3B509FC9CF2C58757BE9FC533
SHA-256	E6EC468E83B8376907BCE551B24F63862CFEB40C0175C68288B141F1245D865D

Key	Value
FileSize	11723372
MD5	5995323F7BB2E5DF370A055E40B72CDA
PackageDescription	Python 3 module to access Nvidia‘s CUDA API (debug extensions) 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 debug extensions for the Python 3 debug interpreter.
PackageMaintainer	Debian NVIDIA Maintainers <pkg-nvidia-devel@lists.alioth.debian.org>
PackageName	python3-pycuda-dbg
PackageSection	contrib/debug
PackageVersion	2018.1.1-4+b5
SHA-1	73E658ED839448E2D6B5B0EF64BF14CF125CCAE5
SHA-256	820E568D9EBE8F2FE49002CF8D357EF9464B7FBEB073DFA2EBD989717C7124EA

Key	Value
FileSize	6779304
MD5	AC091B52FED8A77961A57050FE0AB296
PackageDescription	Python 3 module to access Nvidia‘s CUDA API (debug extensions) 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 debug extensions for the Python 3 debug interpreter.
PackageMaintainer	Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageName	python3-pycuda-dbg
PackageSection	contrib/debug
PackageVersion	2018.1.1-4build2
SHA-1	758EB325B47CB99204593BEF6D2F4C19206C0B28
SHA-256	A99A6258F0A9B1C4CF4B61CA45132A4B346D58D0B842AFB2E440CF12392C75FB

Key	Value
FileSize	6391436
MD5	6BC29D8A6E05A7DCD4D27342505B8785
PackageDescription	Python 3 module to access Nvidia‘s CUDA API (debug extensions) 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 debug extensions for the Python 3 debug interpreter.
PackageMaintainer	Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageName	python3-pycuda-dbg
PackageSection	contrib/debug
PackageVersion	2018.1.1-4build3
SHA-1	7E583D140293BB91D78D6B290EBCA6AF4CC1AF6F
SHA-256	535450A9513B445C6B960AA80E889D619285C950C859ADFDB11AFE7B9405C01A

Key	Value
FileSize	119808
MD5	8610CB0C9A5A484B4BEA977BDB93242A
PackageDescription	module 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.
PackageMaintainer	Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageName	python-pycuda-doc
PackageSection	contrib/doc
PackageVersion	2018.1.1-4build2
SHA-1	80020ED7FA39EC61C4C8E536392338201BA9CDBA
SHA-256	66EBCDE4AB472A2C51AC159F4152B0E1243BB7C87A409F868AC6EB5414590EA8

Key	Value
FileSize	467080
MD5	986E11C92EDD4A81179BF6DD64FC3749
PackageDescription	Python 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.
PackageMaintainer	Debian NVIDIA Maintainers <pkg-nvidia-devel@lists.alioth.debian.org>
PackageName	python3-pycuda
PackageSection	contrib/python
PackageVersion	2018.1.1-4+b2
SHA-1	A1E4C319A849937703C7EAE3EAF6EEAC81BBA12E
SHA-256	7ABB02B7F6393B7C75110F1DB9B4552CA27F5BC02A4256043FDD55CEA6A14F38