stdgpu-contrib 1.3.0+git20220507.32e0517-2 source package in Ubuntu
Changelog
stdgpu-contrib (1.3.0+git20220507.32e0517-2) unstable; urgency=medium * Merge stdgpu-contrib repo into stdgpu repo * Refresh patches from stdgpu in main * Build-depend on nvidia-cuda-toolkit-gcc * Restrict architectures to those with CUDA -- Timo Röhling <email address hidden> Thu, 13 Jul 2023 00:06:05 +0200
Upload details
- Uploaded by:
- Timo Röhling
- Uploaded to:
- Sid
- Original maintainer:
- Timo Röhling
- Architectures:
- amd64 arm64 ppc64el
- Section:
- misc
- Urgency:
- Medium Urgency
See full publishing history Publishing
Series | Published | Component | Section | |
---|---|---|---|---|
Oracular | release | multiverse | misc | |
Noble | release | multiverse | misc | |
Mantic | release | multiverse | misc |
Downloads
File | Size | SHA-256 Checksum |
---|---|---|
stdgpu-contrib_1.3.0+git20220507.32e0517-2.dsc | 2.4 KiB | 128eca159d1350ddc691714d886078547e6341b6544cf7c84f85698de823ed5b |
stdgpu-contrib_1.3.0+git20220507.32e0517.orig.tar.gz | 262.6 KiB | 6f1143acd8262bc9d31bf2e4689ab69b3c62283d6e9c8b2efb284c01ecca7ca1 |
stdgpu-contrib_1.3.0+git20220507.32e0517-2.debian.tar.xz | 11.6 KiB | 588a5185ebfb399995c87b33392d4e0b5a83450b64483121a616c0d52343251a |
Available diffs
No changes file available.
Binary packages built by this source
- libstdgpu-cuda-dev: Efficient STL-like Data Structures on the GPU (CUDA development headers)
stdgpu is an open-source library providing several generic GPU data structures
for fast and reliable data management. Multiple platforms such as CUDA,
OpenMP, and HIP are supported allowing you to rapidly write highly complex
agnostic and native algorithms that look like sequential CPU code but are
executed in parallel on the GPU.
.
This package installs the development headers for the CUDA version.
- libstdgpu-cuda0d: Efficient STL-like Data Structures on the GPU (CUDA backend)
stdgpu is an open-source library providing several generic GPU data structures
for fast and reliable data management. Multiple platforms such as CUDA,
OpenMP, and HIP are supported allowing you to rapidly write highly complex
agnostic and native algorithms that look like sequential CPU code but are
executed in parallel on the GPU.
.
This package installs the shared library that runs on CUDA.
- libstdgpu-cuda0d-dbgsym: debug symbols for libstdgpu-cuda0d