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	121664
MD5	5EFE49327F7B41893841B7AF02F75F66
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	2020.1~dfsg1-1
SHA-1	20A83F606344926C660B842A6C1BE23C771A9596
SHA-256	8781434BDA773A0141FC847C193083B20167249F0E33E2D0A0ED6A414C424FC1

Key	Value
FileSize	119872
MD5	E1BE81A04920A2CCC19D39426D23EAAA
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	2020.1~dfsg1-1
SHA-1	D9EFEAA5B100FB1FE16DAC17E95FA8B4800C338C
SHA-256	27AABC6F3CAEB25C9EEF55153340B0A59046ACE751C1F5FBC6B2FD1723FFA938