Result for 034B14668AACCB44C0092594EA1793311D2E8423

Query result

Key Value
FileName./usr/share/doc/python-pycuda-doc/html/objects.inv
FileSize5191
MD5105E6C45C425174D6F0A1C9BBD7E0337
SHA-1034B14668AACCB44C0092594EA1793311D2E8423
SHA-2561FB1AEF0821BAC82F8F6C3311F48C130B7DF38BAF69CCC86B13D8A02102DA7D0
SSDEEP96:Tc8Vxn96T6T1BipoYuWm8SedCcT5LYH9C2YYLv94iYYaJg9HlyTiQ3saX:QI/iSXuD3T5LF2b14vYaJm6X3sW
TLSHT16BB1A08F4BBE3C9D1701E4E5B50DC26BDF21238C5229F9D4F19E480D1194C164B1897E
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
FileSize174236
MD52EAC8BD5B9E9DBCBEAD75ED0A3C59878
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
PackageVersion2021.1~dfsg-3
SHA-1C7DE09DB5C6681123E9068BE2966EF6C475D773A
SHA-25645AEDE0997C37DF91D89E3AE8A12400BEA438D415FD60F717BC7A09C3DE38AC0
Key Value
FileSize173892
MD5658F298ABE7A6A47B7120C1E1CC72A97
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
PackageVersion2021.1~dfsg-2
SHA-1DEE81AAA5F3A2BD8525C8ABC017CF1969BFBFDBD
SHA-256DF9F9BF0CC18E396CCAB8C89E35C348468D098957F25F4587E9CCDF70A2EFA0A
Key Value
FileSize169508
MD5D56F2F2C0DB4F3E4AFB7EBF7873B9DD8
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
PackageVersion2021.1~dfsg-1
SHA-122A7B1868432C6B088F62D4DE343A287874CE78B
SHA-25620FF36C17CECC791E3F1C627D588061391D9D99334E0EF0898E606A48AE2EED1