Result for 1D6D7C5CB8357F357D1E0FE2BF921BE6FB07AACC

Query result

Key Value
FileName./usr/lib/python3/dist-packages/pycuda/cuda/pycuda-helpers.hpp
FileSize2589
MD5A008DAAB16A2AF8B0600F0AA21AB9C8A
SHA-11D6D7C5CB8357F357D1E0FE2BF921BE6FB07AACC
SHA-25600D0499FBFBC463615896CF066ECC68D0139CE01D5E4291C051AB99EB38E3FFE
SSDEEP24:RR0exeHd+/r1cGc+1ZF5dNZH9ZQkRJZQJQW+RJZQ3YRxnZlkUonZ2iQWUeUdBZJ8:j0exeHU/UclnN9VRJvRJFRNJ0l2Hc1R
TLSHT10051AF6CBCFAFC474D63C1AAABC54401E64EC3E14D96FEB6819D93311D41285EABC4D2
hashlookup:parent-total4
hashlookup:trust70

Network graph view

Parents (Total: 4)

The searched file hash is included in 4 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
FileSize290830
MD5ECD3EFCFE4F75515834707D724A8BE41
PackageDescriptionPython 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.
PackageMaintainerTomasz Rybak <tomasz.rybak@post.pl>
PackageNamepython-pycuda
PackageSectioncontrib/python
PackageVersion2014.1-3
SHA-104E0D8145D3810F0F28BAB86ADB02E7BFD9A6F8B
SHA-256FD0D0950BAE13D67BB17FE667E05609102B44E4B21B78C42D964C0DF4956F9D6
Key Value
FileSize304682
MD5CE0BA381CB2F51A9F332F8D8E8767F8C
PackageDescriptionPython 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.
PackageMaintainerTomasz Rybak <tomasz.rybak@post.pl>
PackageNamepython-pycuda
PackageSectioncontrib/python
PackageVersion2014.1-3
SHA-18951AABF3818022D4EC45C4A1662A43B5ED755EE
SHA-256CA16EB9ADB14EA9379C1705FD381C3E9388031223C58F40F54B8AF67F5678330
Key Value
FileSize306638
MD520BDBAB60A23CABB6F145E5DAE81139A
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.
PackageMaintainerTomasz Rybak <tomasz.rybak@post.pl>
PackageNamepython3-pycuda
PackageSectioncontrib/python
PackageVersion2014.1-3
SHA-1711C5ED5C3AEBDB32C077E013C40061F29A82AA9
SHA-256705403069432FD30956221AAC74170A1853DE5B14F3B4B2C7FECB6D4674E3FB1
Key Value
FileSize295882
MD5CDDA0DCCC9DBCA6143B952EEE0B38FBA
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.
PackageMaintainerTomasz Rybak <tomasz.rybak@post.pl>
PackageNamepython3-pycuda
PackageSectioncontrib/python
PackageVersion2014.1-3
SHA-13813DE52F4C7FB34A679A751F1AB68D4CE3A8E7A
SHA-256BB42B676C5A967925887C2604B20645485086CB062B8A2E5060DA030A87CC087