Result for 001475FDBE733C7DAE316D051EA31D7590C5A50F

Query result

Key Value
FileName./usr/share/nvidia-cuda-toolkit/samples/3_Imaging/NV12toBGRandResize/NsightEclipse.xml
FileSize2396
MD5C080341FB5DA176FD01E433A7C19296F
SHA-1001475FDBE733C7DAE316D051EA31D7590C5A50F
SHA-256B52443A5FDADA58887278C6C31BAD7F9BA8D01245E9C6D7BF4AC1F2C3A045E56
SSDEEP48:cJlDF+HIzIunADkfdkJtmeNVebTw5DxexRpEf6BkVgp3b+NbHb8UuEXKtEXKZ4KM:23+SAoUubTw5DxelBkapL+NbHb8rEXK6
TLSHT1D5411066D4F9E702E2C8A7432A84614F1F5AD09B588B710CB6DD4B789F84CC4816B7A0
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
MD5BBCC3B83FC0D6A7445D1BFD5D60A7C30
PackageArchx86_64
PackageDescriptionNVIDIA® CUDA™ is a general purpose parallel computing architecture that leverages the parallel compute engine in NVIDIA graphics processing units (GPUs) to solve many complex computational problems in a fraction of the time required on a CPU. It includes the CUDA Instruction Set Architecture (ISA) and the parallel compute engine in the GPU. To program to the CUDA™ architecture, developers can, today, use C++, one of the most widely used high-level programming languages, which can then be run at great performance on a CUDA™ enabled processor. Support for other languages, like FORTRAN, Python or Java, is available from third parties. This package contains numerous CUDA code samples (formerly CUDA SDK).
PackageMaintainerwally <wally>
PackageNamenvidia-cuda-toolkit-samples
PackageRelease1.2.mga7.nonfree
PackageVersion10.1.168
SHA-1B7849B54827B40E5EDE23442BE4FA8E81469EA8F
SHA-2569804C6498970CA54F95A6A5A083B0DC7D293A0C699608BB65731BF7265BCA9A6
Key Value
MD55263491108C084801CD43EEA077F1409
PackageArchx86_64
PackageDescriptionNVIDIA® CUDA™ is a general purpose parallel computing architecture that leverages the parallel compute engine in NVIDIA graphics processing units (GPUs) to solve many complex computational problems in a fraction of the time required on a CPU. It includes the CUDA Instruction Set Architecture (ISA) and the parallel compute engine in the GPU. To program to the CUDA™ architecture, developers can, today, use C++, one of the most widely used high-level programming languages, which can then be run at great performance on a CUDA™ enabled processor. Support for other languages, like FORTRAN, Python or Java, is available from third parties. This package contains numerous CUDA code samples (formerly CUDA SDK).
PackageMaintainertmb <tmb>
PackageNamenvidia-cuda-toolkit-samples
PackageRelease1.mga7.nonfree
PackageVersion10.1.168
SHA-1F469BAAA0D3E190716B66B9D312BD4622F445DA5
SHA-256FEA96096F66373C5E67B2C818C4D276855AA6AA8ABFE7BAD0348171DE2D4C07B