Result for 2328672F87C946171C3795391E053332AF180B4A

Query result

Key Value
FileName./usr/lib/python3/dist-packages/pycuda/__init__.py
FileSize106
MD5C4D90E6CDEA7B6C23F5122A6FDF49EE6
SHA-12328672F87C946171C3795391E053332AF180B4A
SHA-256985BF22D97DD50AEE94FCB44ADE1CC567B24344772C8B93593D242495ACE8ABF
SSDEEP3:xrFLMrgurMw79u2sqrr9x+rjaNHXFq7sQMFqKQMwIn:tFL85t9u2sQp8rjaN3Fq7sQEqKQan
TLSHT13EB012138108A4D81040E8CF2175338172407F000F144812E534F300F713C0803FCFE5
hashlookup:parent-total3
hashlookup:trust65

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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
FileSize329524
MD5E39E829BAED401402799183298168ED6
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
PackageVersion2022.1~dfsg-1+b2
SHA-1B3D937C10BD617F39313EF47652B115BC308CA8D
SHA-25683CE93FCC2DBBC2794C362EEA69DCDB61E037AA823C4929F0DDB7A77B503615D
Key Value
FileSize329868
MD5B20771B302CCA183D48CD62C2A0BD199
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
PackageVersion2022.1~dfsg-1+b1
SHA-1E9D4E75818EF362C4825EE91D654B9025D1911BD
SHA-256C5D555ADD3F52F843FF7D322831B2EA5CB28BE79EE931CA8043D859596451DE5
Key Value
FileSize316184
MD52759CA0B5317934D9C1E387CFADEE0E0
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
PackageVersion2022.1~dfsg-1+b2
SHA-13E6979DE298CF0818067A4899F2B1BBAD69D23CC
SHA-256AF4FD2CB4EFB5B2E9A1ED4352075823F959EE5E22F3FF8140215C3C6E79CE599