Result for 3D464D2B73185616C43CF32238C806446972C195

Query result

Key Value
FileName./usr/lib/python3/dist-packages/pycuda/sparse/pkt_build.py
FileSize2684
MD5CC291813C6E0B3DAB70E99CD5DE4036E
SHA-13D464D2B73185616C43CF32238C806446972C195
SHA-256827846AA3646CCF78A04809302277D1AA3DED6D58E16CBBE191B4ACAD20378FC
SSDEEP48:dVbX3Ez0iE004Wn+o4IJISTzgcFdbrULeYgr+rAbbkS6v8cFsyV4IbINWItEvm85:dVbX3Ez0iE004Wn+NISSTzvnr47drAb0
TLSHT17451AB1E461FA5DDF6FBAD64087C5B42603B2A5B49806500F75DCC200F9E2B5F22ADA5
hashlookup:parent-total4
hashlookup:trust70

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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