A key enabler of innovation and discovery for many scientific researchers is the ability to explore data and express ideas quickly as software prototypes. Tools and techniques that reduce the “time to insight” are essential to the productivity of researchers. At the same time massive increases in data volumes and computational needs require a continual focus on maximizing code performance. To manage these competing requirements, today’s researchers often find themselves using a heterogeneous and complex mix of programming languages, development tools, and hardware.
The C++ programming language is used for many numerically intensive scientific applications. A combination of performance and solid backward compatibility has led to its use for many research software codes over the past 20 years. Despite its power, C++ is often seen as difficult to learn and inconsistent with rapid application development. Exploration and prototyping is slowed down by the long edit-compile-run cycles during development.
Over the last decade, toegher with collaborators, we have developed an interactive, interpretative C++ (aka REPL) based on LLVM and clang. Amongst our research goals are to
We are looking for interested and passionate undergrad and graduate students. Fellowships (and open projects) currently available via IRIS-HEP.
23 February 2021
Recording from February discussion on Calling C++ Libraries from D
19 February 2021
GSoC projects posted
11 January 2021
Cling 0.8 released
21 December 2020
Interactive C++ for Data Science with Cling
3 December 2020
CaaS meeting 17:00
30 November 2020
Cling on the LLVM blog
22 October 2020
CaaS meeting 18:00