Result for 3FD09CDCCB369E8CBEE462BAC4CC7C6623D0E6BC

Query result

Key Value
FileName./usr/lib/python3/dist-packages/pycuda/curandom.py
FileSize42619
MD55080472459EF8C3272962C6B4970B2D5
SHA-13FD09CDCCB369E8CBEE462BAC4CC7C6623D0E6BC
SHA-2565D5E23A4260F0DC2DFE6ACC047C65FDB7C12D29E6DC93AF9C12999FB767B13DA
SSDEEP768:XzxnyTniL2xDSAV3j4Mgbg8Rt9nIZDUT+CWDofhXmikCmr:VyTniL2xl4Mgbg8Rt9nItUT/WDofhvkX
TLSHT19513A7A98C8058539A83D43959DB6C53221261075A4C7CFBB87C51E53F0E22EA3F9FED
hashlookup:parent-total2
hashlookup:trust60

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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
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