Result for 017A9E6C2B3937637C607306BDC8B7842F958A05

Query result

Key Value
FileName./usr/share/doc/python3-pycuda/copyright
FileSize5917
MD5EC8EF82F4986047B852A33E9937B2154
SHA-1017A9E6C2B3937637C607306BDC8B7842F958A05
SHA-2560C76F1C191C99E7779BA0C7D167342193DD0546E7866CA31766EA34684CF12C6
SSDEEP96:j0r4Tvm+/WlyNl4reeVTG8NvP/4YV04gPzHFcVFqpk4XV7XP+4KQHLog:j0G++zNOr/c8NvPV0DPzHa0W4XFHKQHx
TLSHT10CC1E76F734407B21AD027D23F9AA4CEB34FB15AF7379AC4B45CC14D273A429827A5A0
hashlookup:parent-total3
hashlookup:trust65

Network graph view

Parents (Total: 3)

The searched file hash is included in 3 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
FileSize329116
MD5DBFB5E9DCBB1E29E6F6CBDD9B0F15272
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
PackageVersion2022.2.2~dfsg-2+b1
SHA-1CD0148477C4C6AE7F6219E19AC93E6525E224641
SHA-256DB7F7B242CE5FAF91B542B1D8EDEBDAA213BC4C99334E2B316E1D035F2E92A0B
Key Value
FileSize314308
MD5017D08C1CB5EE436FD7377EC13B1F147
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
PackageVersion2022.2.2~dfsg-2+b1
SHA-1F6586DE689141BB88F93E9A6FF9CD3D28765186E
SHA-256D40BBD22F382C1DCA63A03BDC16DDAEDEEAFC1E00C973078C672FEA072AB8650
Key Value
FileSize183360
MD58F9F5237510378269CA1E096FE030F5E
PackageDescriptionmodule 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.
PackageMaintainerDebian NVIDIA Maintainers <pkg-nvidia-devel@lists.alioth.debian.org>
PackageNamepython-pycuda-doc
PackageSectioncontrib/doc
PackageVersion2022.2.2~dfsg-2
SHA-12DDEBB7F38BC33C83AC6361524343DAEBD906861
SHA-25687AAAC16EE8F39D3BAE6F9504F886E802805D359C76EE7885E9A019F62BE8BB1