GSoC’17: Come and code a STE||AR Summer with us!

The STE||AR Group is honored to have been selected as one of the 2017 Google Summer of Code (GSoC) mentor organizations! This program, which pays students over the summer to work on open source projects, has been a wonderful experience for the past three years that we have been accepted by the program. Interested students can find out more about the details of the program on GSoC’s

GSoC 2016 Participants Announced!

We can now announce the participants in the STE||AR Group’s 2016 Google Summer of Code! We are very proud to announce the names of those 6 students who this year will be funded by Google to work on projects for our group.

These recipients represent only a handful of the many excellent proposals that we had to choose from. For those unfamiliar with the program, the Google Summer of Code brings together ambitious students from around the world with open source developers by giving each mentoring organization funds to hire a set number of participants. Students then write proposals, which they submit to a mentoring organization, in hopes of having their work funded.

GSoC’16: Come Enjoy a STE||AR Summer of Code!

The STE||AR Group is honored to have been selected as one of the 2016 Google Summer of Code (GSoC) mentor organizations! This program, which pays students over the summer to work on open source projects, has been a wonderful experience for the past two years that we have been accepted by the program. Interested students can find out more about the details of the program on GSoC’s

GSoC 2015 Results: Success!

This summer has been an exciting time for the STE||AR Group’s GSoC mentors and students alike! We were very pleased with the dedication and effort of all five of our participants. Our students made contributions to three of our software products: HPX, a distributed C++ runtime system which comes with a standards compliant API and allows users to scale their applications across thousands of machines; LibGeoDecomp, an auto-parallizing library for petascale computer simulations which is able to take advantage of HPX to better adapt fluctuating workloads to the system; and LibFlatArray, a highly efficient multidimensional array library which provides an object-oriented interface but stores data in a vectorization-friendly Struct-of-Arrays format.