Parents (Total: 8)

The searched file hash is included in 8 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
FileSize	304682
MD5	CE0BA381CB2F51A9F332F8D8E8767F8C
PackageDescription	Python 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.
PackageMaintainer	Tomasz Rybak <tomasz.rybak@post.pl>
PackageName	python-pycuda
PackageSection	contrib/python
PackageVersion	2014.1-3
SHA-1	8951AABF3818022D4EC45C4A1662A43B5ED755EE
SHA-256	CA16EB9ADB14EA9379C1705FD381C3E9388031223C58F40F54B8AF67F5678330

Key	Value
FileSize	274644
MD5	ED8AD29029BB381193C32B3F4033D624
PackageDescription	Python 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.
PackageMaintainer	Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageName	python3-pycuda
PackageSection	contrib/python
PackageVersion	2013.1.1+git20140310-1ubuntu1
SHA-1	CC44752730EAE48E9322FD9E9E6E8627120EDD40
SHA-256	B56B41089750487F10DC079C86C92F32FA0E895C44CB1C93819F29AA2A259147

Key	Value
FileSize	290830
MD5	ECD3EFCFE4F75515834707D724A8BE41
PackageDescription	Python 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.
PackageMaintainer	Tomasz Rybak <tomasz.rybak@post.pl>
PackageName	python-pycuda
PackageSection	contrib/python
PackageVersion	2014.1-3
SHA-1	04E0D8145D3810F0F28BAB86ADB02E7BFD9A6F8B
SHA-256	FD0D0950BAE13D67BB17FE667E05609102B44E4B21B78C42D964C0DF4956F9D6

Key	Value
FileSize	270836
MD5	824839BAE101E1F595D7BBFEC4DC0289
PackageDescription	Python 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.
PackageMaintainer	Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageName	python-pycuda
PackageSection	contrib/python
PackageVersion	2013.1.1+git20140310-1ubuntu1
SHA-1	ED2B2716DDD78BA7CCBF03C81D3A325B9332C344
SHA-256	0FFF8E40AFA02B86ADDE6FE1297EA194CC644688EB27E4C9B282F40A3B84462C

Key	Value
FileSize	286710
MD5	55C4D78828DD6C5D174DFA73AB3A8362
PackageDescription	Python 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.
PackageMaintainer	Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageName	python-pycuda
PackageSection	contrib/python
PackageVersion	2013.1.1+git20140310-1ubuntu1
SHA-1	365759025B6938D917128F6A5D9A7120493AA77D
SHA-256	A890F86665FF33AED134EB603581ADD813BAE668D3AB30AEB8A0830AEF2B812E

Key	Value
FileSize	289846
MD5	2D889EAE840CC2AC22595A7F852665AB
PackageDescription	Python 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.
PackageMaintainer	Ubuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageName	python3-pycuda
PackageSection	contrib/python
PackageVersion	2013.1.1+git20140310-1ubuntu1
SHA-1	F02966E5E806DD6C1C75495A0A69B246E97D615C
SHA-256	2F387E80DF0F14AB9DB174CC2C5433792C7CE8211EC60DBF367FAC39D2A33D27

Key	Value
FileSize	306638
MD5	20BDBAB60A23CABB6F145E5DAE81139A
PackageDescription	Python 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.
PackageMaintainer	Tomasz Rybak <tomasz.rybak@post.pl>
PackageName	python3-pycuda
PackageSection	contrib/python
PackageVersion	2014.1-3
SHA-1	711C5ED5C3AEBDB32C077E013C40061F29A82AA9
SHA-256	705403069432FD30956221AAC74170A1853DE5B14F3B4B2C7FECB6D4674E3FB1

Key	Value
FileSize	295882
MD5	CDDA0DCCC9DBCA6143B952EEE0B38FBA
PackageDescription	Python 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.
PackageMaintainer	Tomasz Rybak <tomasz.rybak@post.pl>
PackageName	python3-pycuda
PackageSection	contrib/python
PackageVersion	2014.1-3
SHA-1	3813DE52F4C7FB34A679A751F1AB68D4CE3A8E7A
SHA-256	BB42B676C5A967925887C2604B20645485086CB062B8A2E5060DA030A87CC087