Result for 0122715C85FA20030CFF3B0B2887FE11C38729EC

Query result

Key Value
FileName./usr/share/nvidia-cuda-toolkit/samples/0_Simple/matrixMulDrv/readme.txt
FileSize433
MD5AC93D6884320189220D82304F3C35C1F
SHA-10122715C85FA20030CFF3B0B2887FE11C38729EC
SHA-256AB1A38AA9FAEA79D79892E9EEA00A88B43F0D000BFCC4E9882C091CED02F32FE
SSDEEP12:dwJTJ6CLXqm/4nt6WqVl6sJlf6+AFtWFnKmHl4yce:d8QCLL0toVl6sJlf6bvCnKgl1ce
TLSHT1E1E0F187C6042A1101F78953D2AF59E19D6D8318BF9D4C169D0CE331C649D598B7F7C8
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