Result for 0C666507E3FEBC0F6344A584ED9CC2D5CE292163

Query result

Key Value
CRC323C47F11D
FileName./usr/share/doc/python-pycuda-doc/examples/hello_gpu.py
FileSize582
MD5F55DB0EB035E54AA6AC847D411D9EB67
OpSystemCode{'MfgCode': '1006', 'OpSystemCode': '362', 'OpSystemName': 'TBD', 'OpSystemVersion': 'none'}
ProductCode{'ApplicationType': 'Operating System', 'Language': 'English', 'MfgCode': '1006', 'OpSystemCode': '185', 'ProductCode': '9736', 'ProductName': 'Mandriva Linux Powerpack', 'ProductVersion': '2010'}
RDS:package_id9736
SHA-10C666507E3FEBC0F6344A584ED9CC2D5CE292163
SHA-256A02F76E4C75364F764874CA2261F85C79B14E5F3F54B565A373BB3BA4066DBE6
SSDEEP12:dFSMr4VtHOeBf659LZiDVBUQTW6NVW6NZ8KHwAaJN5:d90VROeBC5Rc7F3PX8FJf
SpecialCode
TLSHT173F0C04726B820D31D64F8D15BB923B613B264A02FC41C15E97FA1A0DBA522F50AD2FF
dbnsrl_legacy
insert-timestamp1648568258.3705823
sourceRDS_2022.03.1_legacy.db
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
FileSize119956
MD523CDA4ED64E49A236DB26EEFFAC2B1FA
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.
PackageMaintainerUbuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageNamepython-pycuda-doc
PackageSectioncontrib/doc
PackageVersion2013.1.1+git20140310-1ubuntu1
SHA-17C32F16E8D9F9B42EE7B8391513C4F4133317A55
SHA-256F1E5743A8D81E47F415F60B257194F92B88E1D694117431EC5A9A6268AB3783C
Key Value
FileSize121238
MD5C4E65F38C34CDFB41E9E87C44B27A227
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.
PackageMaintainerTomasz Rybak <tomasz.rybak@post.pl>
PackageNamepython-pycuda-doc
PackageSectioncontrib/doc
PackageVersion2014.1-3
SHA-11BDB201A404831B25FF18CC3D1A3D1D96C30A4CA
SHA-256D22CCAA27B9C7C511F994AE05367E43D665EB7F35F8084FA6E7BFB6A05621D04