| Key | Value |
|---|---|
| FileName | ./usr/share/nvidia-cuda-toolkit/samples/0_Simple/simpleVoteIntrinsics/readme.txt |
| FileSize | 231 |
| MD5 | 4AED5F5A25BA668E38817F25459329B0 |
| SHA-1 | 006AEB45637FC5608339C24B13B0FE32817B21FD |
| SHA-256 | 641EFC0BCC3831F5A64F84930A7BBDAB77323900F5673126A8C636FFDFF31BD3 |
| SSDEEP | 6:deAhkGtaKEtFEDrn5HMiMDWNvN0+oJOUKDQZ:deAhBCFGrniv0N0ROTDQZ |
| TLSH | T115D0A72431964298C94A46F2566EA545142CD40530DB065A572D82778500A75D1BF774 |
| 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 |