Key | Value |
---|---|
FileName | ./usr/share/nvidia-cuda-toolkit/samples/7_CUDALibraries/nvJPEG/readme.txt |
FileSize | 179 |
MD5 | 87D2875E98C584DBDE62EACAAE260A12 |
SHA-1 | 00C4B68C934A4210FC11194FB8F0BEDA3CFEE0C4 |
SHA-256 | 6615E3420A2FEE096BB64EA048BCF6391FABDCC7BF2D8475F8AE4897B2D05276 |
SSDEEP | 3:dfxTSudFW9QXU3DqQ9tFEmTOIH5ABvHLdbri2LGX+cLuAIzlKPrD1geGX+cvn:d5uu2GXUTj9tFEWeBvrdb2EA+5AOKPto |
TLSH | T100C080BCD101324143D9487721EFB44D1667A0311157CDA5075E4574950ADF2557939F |
hashlookup:parent-total | 2 |
hashlookup:trust | 60 |
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 |
---|---|
MD5 | BBCC3B83FC0D6A7445D1BFD5D60A7C30 |
PackageArch | x86_64 |
PackageDescription | NVIDIA® 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). |
PackageMaintainer | wally <wally> |
PackageName | nvidia-cuda-toolkit-samples |
PackageRelease | 1.2.mga7.nonfree |
PackageVersion | 10.1.168 |
SHA-1 | B7849B54827B40E5EDE23442BE4FA8E81469EA8F |
SHA-256 | 9804C6498970CA54F95A6A5A083B0DC7D293A0C699608BB65731BF7265BCA9A6 |
Key | Value |
---|---|
MD5 | 5263491108C084801CD43EEA077F1409 |
PackageArch | x86_64 |
PackageDescription | NVIDIA® 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). |
PackageMaintainer | tmb <tmb> |
PackageName | nvidia-cuda-toolkit-samples |
PackageRelease | 1.mga7.nonfree |
PackageVersion | 10.1.168 |
SHA-1 | F469BAAA0D3E190716B66B9D312BD4622F445DA5 |
SHA-256 | FEA96096F66373C5E67B2C818C4D276855AA6AA8ABFE7BAD0348171DE2D4C07B |