Result for 004E2F2B0AD4D4B289AEFCE87AC895CCD5D23043

Query result

Key Value
FileName./usr/share/nvidia-cuda-toolkit/samples/2_Graphics/simpleGLES_screen/Makefile
FileSize11708
MD525FF1E06F8030C002025832E36C26AD5
SHA-1004E2F2B0AD4D4B289AEFCE87AC895CCD5D23043
SHA-25647E64FB1235FD70B3473DD594E3094D86BF5942F4AFE18C25B43627F26879E20
SSDEEP192:5kHQ85iECBftAmA8VX+hTT/5/EMLGKhmbXU/LJCt0smN/2x/4N8/Ad0UAF2w/4d1:5kQ88pAmAiX+hPh/PLGKhmbXU/LJCt0r
TLSHT1A33293A6332437B20F1A80CB334A7757A55B84577F2FA927B40C4BE42B27A5AC319E54
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