Parents (Total: 2)

The searched file hash is included in 2 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
FileSize	12071548
MD5	FEC91AD3CCF131B1F337CA515360B182
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+b1
SHA-1	F507BBDCDABD3C33364086BD0DB2E78CAADA8576
SHA-256	E3D145C58515FAFFF2BA70C68ECF9E126B2DA2862AA4E630EC3C651B9AB42ECA

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