HPX’s Season of Docs 2021

By Rachitt Shah

HPX was recently selected to be part of Google’s Season of Docs (GSoD), a program designed to improve the documentation of open source software, as well as being a Google Summer of Code organization.

GSoD aims to cover and create the documentation gaps faced by organizations due to various reasons, alongside giving technical writers an avenue to showcase their skills.

I will be helping in the organization and update of the prior documentation to make it into a more navigable and to provide a user-friendly structure, which many users have had issues with using the current documentation. I will work closely with the HPX team and our users to collect feedback, find user pain-points, and improve preexisting docs, which mainly comprise of the build instructions.

Alongside, I would create a “design document” containing guidelines for how to add new content to the documentation: tips on how to structure new sections, general guidelines on what sort of content should be presented in what chapters, etc. The project may also include content rearrangement and a change of hierarchy, if the users find it is needed. 

I am currently working on a timeline and action items and researching about the possible shift to another documentation platform.

I am reachable at rachitt01@gmail.com or on the IRC as rachitt_shah, please contact me to suggest changes to the documentation or to provide feedback. We can always benefit from your ideas.

About me, I’m an undergrad studying electronics as my major, and I’m a casual sport programmer as well. I’ve been a product manager and venture capital intern in the past, and done Google Summer of Code with OpenAstronomy.

GSoC 2021 Participants Announced!

It is time to announce the participants for in the STE||AR Group’s 2021 Google Summer of Code! We are very proud to announce the names of the 2 students this year who will be funded by Google to work on projects for our group.

These recipients represent the very best 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.

Below are the students who will be working with the STE||AR Group this summer listed with their mentors and their proposal abstracts.


Akhil J Nair, Army Institute Of Technology ( Savitribai Phule Pune University)


Giannis Gonidelis

Hartmut Kaiser

Project: Adapting algorithms to C++ 20 and Ranges TS

I’m Akhil J Nair, a third year undergrad studying computer engineering at AIT, Pune. I’ll be working with the STE||AR group this summer, focusing on the algorithms part of HPX, working on tasks such as adapting the parallel algorithms to C++ 20, adding range overloads, sentinel overloads etc. The algorithms would be adapted to use the tag_invoke customization point mechanism and the C++ 20 overloads will be added according to the C++ 20 Standard. The ranges overloads will also be added as proposed in the C++ extensions to ranges. Adding sentinel overloads and separating the segmented algorithms for the few remaining algorithms will also be done. I’m hoping this would serve as an entry point for me to HPX and the wider world of HPC in general and I look forward to contributing and learning a lot over the coming months.


Srinivas Yadav, Keshav Memorial Institute of Technology, Hyderabad, India


Nikunj Gupta

Patrick Diehl

Project:  Add vectorization to par_unseq implementations of Parallel Algorithms

I am Srinivas Yadav currently pursuing my Bachelors in Computer Science at KMIT, Hyderabad, India. I will be working with STE | | AR group for HPX this summer in the area of vectorization for parallel algorithms. Current hpx parallel algorithms do not support vectorization. Vectorization allows the algorithms to use the cpu vector registers and hence performance may be improved by utilising most of the cpu resources and allows us to exploit another level of parallelism. This project aims to implement the support for parallel algorithms with explicit vectorization with new `simd` execution policy by using the c++ experimental simd extensions. I hope contributing to HPX would serve me as a stepping stone to the world of HPC and I am looking forward to learning and contributing more over the coming months.