| Key | Value |
|---|---|
| FileName | ./usr/lib64/cuda-toolkit-root-dir/lib64/libnppig.so.11.4.0.110 |
| FileSize | 44 |
| MD5 | 19AFD7F6FE08E70012B7206F2CD0C41A |
| SHA-1 | 0E9E088E70C50937B66713C1DEB378E32B523CBF |
| SHA-256 | 47C3C4987143E2DA06F6D863C92EA93C4D9F352A081DE35454C99600D4ECC7C6 |
| SSDEEP | 3:gCD/piKtRTV:X/L1 |
| TLSH | |
| 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 | 77288B73382A811C17BC6C534D5AF84B |
| 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 the development files needed to build programs that make use of CUDA. |
| PackageMaintainer | ghibo <ghibo> |
| PackageName | nvidia-cuda-toolkit-devel |
| PackageRelease | 1.mga8.nonfree |
| PackageVersion | 11.4.3 |
| SHA-1 | 46264026A5D578719AAE3BFEAFE22728CD9A8415 |
| SHA-256 | B8ADE1366CCC1BA26385FE8AE67C95752A589F1A269D30D6DE4E7DEC9A3B5B42 |
| Key | Value |
|---|---|
| MD5 | DA18F12D635B53966BA58EF4D38DD84A |
| 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 the libraries and attendant files needed to run programs that make use of CUDA. |
| PackageMaintainer | ghibo <ghibo> |
| PackageName | nvidia-cuda-toolkit |
| PackageRelease | 1.mga8.nonfree |
| PackageVersion | 11.4.3 |
| SHA-1 | ECF62406B22DD6176CAEB5F94D0079C9D8CA7772 |
| SHA-256 | B9111E42A9B8DB236B556A1EF8D93D8B7DC3B2B5CADBC550CCAF4808B9D94F4C |