Hello,
I am Saurabh, co-founder of Hackr.io. Hackr.io is a programming community & a great place to find the best online programming courses and tutorials. It's a one stop solution for tutorial recommendations with 5000+ tutorial of more than 140 programming languages.
I was looking at your learning resources page and found it pretty useful. I believe that Hackr.io would be really useful to the developer community in finding the right programming course/tutorial and would make a nice addition to your resource page.
Hackr is also listed on other esteemed websites like Lehigh University's resource page and official Official Python wiki page to name a few.
Thanks for the list of great resources you have compiled. Enjoy your week:)
Spack is a flexible package manager that supports multiple versions,
configurations, platforms, and compilers. It's perfectly suited for
complex software toolchains as often seen on clusters and seamlessly
allows to combine C/C++, Fortran, Python, R, ... projects and
bindings with a high user-control on variants, flags and dependencies
of all packages.
**alpaka** and **cupla** are two coupled libraries that allow
programming accelerator hardware (GPUs, Xeon Phi, etc.) via a
common, single-source, performance-portable, standard C++11
programming model.
alpaka/cuplda are used in various scientific codes, e.g.
PIConGPU, HASEonGPU, ISAAC and Mephisto.
A list of publications (including OA links) explain the concepts
behind alpaka/cupla:
* DOI:10.1109/IPDPSW.2016.50 (http://arxiv.org/abs/1602.08477),
paper in AsHES2016
* DOI:10.5281/zenodo.49768 (thesis: diploma)
* DOI:10.1007/978-3-319-67630-2_36 (https://arxiv.org/abs/1706.10086),
paper in ISC17 (P3MA)
* DOI:10.1007/978-3-319-46079-6_21 (https://arxiv.org/abs/1606.02862),
paper in ISC16 (IWOPH)
* Live-Porting from CUDA to alpaka/cupla, talk in GTC2016:
https://mygtc.gputechconf.com/events/32/schedules/2792
Video: http://on-demand.gputechconf.com/gtc/2016/video/S6298.html
