Elements: C++ as a service - rapid software development and dynamic interoperability with Python and beyond

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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 realize the potential science from novel scientific apparatus. Programming language usability and interoperability are omni-disciplinary issues affecting today's scientific research community. As a result, a common approach across many scientific fields research is for scientists to program in Python, while steering kernels written in C++. This C++ as a service (CaaS) project brings a novel interpretative technology to science researchers through a state-of-the-art C++ execution environment. CaaS will enable both beginners and experts in C++. It enables higher-productivity in development and extends the interactive education and training platform for programming languages. CaaS will enable existing technologies as well as truly new development and analysis approaches. CaaS will directly support grow cyber-capabilities that advance scientific research across a broad range of pursuits.Performance-focused languages, such as C++, are a critical infrastructure component for many scientific fields that have either large computing challenges or the need for low latency for results. The productivity of data scientists can be dramatically increased by an easy to use dynamic programming and development environment, together with a fully featured interoperability layer. The CaaS project provides a dynamic C++ execution environment and enables runtime language interoperability between C++ and other languages, such as Python, through a native-like, dynamic environment. CaaS provides seamless offloading of work in a heterogeneous computing environment, including hardware accelerators, which is more and more often required by today's researchers. These advances will enable researchers to more easily develop in, and use, large C++ codebases that are critical infrastructure components in many scientific fields. CaaS also allows true interoperability with C++ in Jupyter notebooks, and a robust prototyping environment for C++ developments. It encourages analysis and code sharing and facilitates scientific provenance tracking. By reducing the technical burden of development, researchers can focus instead on their scientific productivity. More broadly, notebook-based training in C++, or in a mixed programming environment that includes C++, is a key functionality. Enhancements in technical training will enable national advancements in science, technology, engineering, and mathematics capabilities.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.