Parents (Total: 4)

The searched file hash is included in 4 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
FileSize	174236
MD5	2EAC8BD5B9E9DBCBEAD75ED0A3C59878
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	Debian NVIDIA Maintainers <pkg-nvidia-devel@lists.alioth.debian.org>
PackageName	python-pycuda-doc
PackageSection	contrib/doc
PackageVersion	2021.1~dfsg-3
SHA-1	C7DE09DB5C6681123E9068BE2966EF6C475D773A
SHA-256	45AEDE0997C37DF91D89E3AE8A12400BEA438D415FD60F717BC7A09C3DE38AC0

Key	Value
FileSize	173892
MD5	658F298ABE7A6A47B7120C1E1CC72A97
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	Debian NVIDIA Maintainers <pkg-nvidia-devel@lists.alioth.debian.org>
PackageName	python-pycuda-doc
PackageSection	contrib/doc
PackageVersion	2021.1~dfsg-2
SHA-1	DEE81AAA5F3A2BD8525C8ABC017CF1969BFBFDBD
SHA-256	DF9F9BF0CC18E396CCAB8C89E35C348468D098957F25F4587E9CCDF70A2EFA0A

Key	Value
FileSize	169508
MD5	D56F2F2C0DB4F3E4AFB7EBF7873B9DD8
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	Debian NVIDIA Maintainers <pkg-nvidia-devel@lists.alioth.debian.org>
PackageName	python-pycuda-doc
PackageSection	contrib/doc
PackageVersion	2021.1~dfsg-1
SHA-1	22A7B1868432C6B088F62D4DE343A287874CE78B
SHA-256	20FF36C17CECC791E3F1C627D588061391D9D99334E0EF0898E606A48AE2EED1

Key	Value
FileSize	183360
MD5	8F9F5237510378269CA1E096FE030F5E
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	Debian NVIDIA Maintainers <pkg-nvidia-devel@lists.alioth.debian.org>
PackageName	python-pycuda-doc
PackageSection	contrib/doc
PackageVersion	2022.2.2~dfsg-2
SHA-1	2DDEBB7F38BC33C83AC6361524343DAEBD906861
SHA-256	87AAAC16EE8F39D3BAE6F9504F886E802805D359C76EE7885E9A019F62BE8BB1