About the Book

One of the key goals in high-performance and distributed software engineering is to leverage the specific capabilities of the target hardware to the extent possible. Today’s systems are typically heterogeneous, where one or more architectures may be present within a single system, such as conventional CPU cores combined with accelerators such as GPUs and FPGAs. Although parallel computing itself has reached a high level of maturity, as we move toward exascale computing and beyond, challenges similar to those that plagued the earliest days of parallel and distributed computing are beginning to resurface: Leveraging heterogeneity while balancing performance, software portability, and developer productivity (P3).

This tutorial–delivered as a Python Sphinx book that rebuilds on all changes to the text and underlying source code–provides hands-on experience in developing high-performance and embedded software for heterogeneous architectures using Intel’s oneAPI reference implementation of the Khronos SYCL standard in conjunction with state-of-the-art software engineering methods. By raising the abstraction level via its unified application programming interface (API), oneAPI makes it easier to develop portable high-performance software for systems with embedded hardware accelerators, such as GPUs and FPGAs.

Build Status

GitHub Pages and Release PDF

See github.com/LoyolaChicagoBooks/unoapi/actions

Distribution

Web Version

See unoapi.org

Book Version

See github.com/LoyolaChicagoBooks/unoapi/releases/latest/download/UnoAPI.pdf.

Example Source Code

Other Systems Code Examples - C/C++

Our EduHPC 2022 Paper on UnoAPI

https://ieeexplore.ieee.org/document/10027537

Preprint of our EduHPC 2022 Paper on UnoAPI

https://doi.org/10.6084/m9.figshare.21200464.

If you find our work useful, please consider citing the above paper. We will have an updated way of citing this work soon.

Please do not hesitate to contact us with any questions, regardless of whether you find us useful or not.

Motivation for Our Work

This is not all-inclusive.

Tenets:

  • Who are the next generation of research software engineers and want to consider HPC careers?

  • Most graduates drawn to modern web development, data science, and machine learning jobs. All require HPC knowledge, too.

  • Most graduates learning about cool languages that offer higher-order thinking, e.g. Scala, Go, Rust, and numerous scripting languages. This is a first step toward bringing them back to C++.

In addition:

  • HPC itself is still cool with heterogeneous computing and “novel architectures* having a renaissance.

  • The most modern languages still punt to C to provide acceleration; C++ raises the level of abstraction without compromising performance.

  • Research software engineers want to balance performance, portability, and productivity.

Editors/Contributors

Contributors

Note

There are others; however, I am waiting for their initial pull requests (for chapters) and ORCIDs

  • Raymundo Hernandez Esparza, Postdoctoral Appointee, Argonne National Laboratory, Leadership Computing Facility

  • Maria Pantoja, Associate Professor, CalPoly, Computer Engineering

  • Erik Pautsch, PhD Student, Loyola University Chicago, Compmuter Science

  • Silvio B. Rizzi, Computer Scientist, Argonne National Laboratory, Leadership Computing Facility

  • Alvaro Vazquez-Mayagoitia, Principal Software Development Specialist, Argonne National Laboratory, Leadership Computing Facility

  • Jorge Velez, Undergraduate CS Student, University of Illinois at Urbana-Champaign, Computer Science

AI Disclosure

Note

This text contains a mix of original writing and programming with strategic use of Chat-GPT4 via intelligent/clever prompting. All examples will be available in our repository with an appropriate cmake build file and tests. We will also make our prompts and analysis available, similar to what we have done for our recent ongoing study of Chat-GPT4 and Systems Programming. See https://doi.org/10.6084/m9.figshare.22257274.

Acknowledgements

Thanks to Intel Corporation for their support of our work (George Silva, Omar Toral, Ben Odom).

Topics

These are the planned chapters:

  • Parallel Programming Principles

  • Development Environment [minimum friction approaches]

  • Software Engineering

  • Modern C++ as a Better C/C++

  • Data Parallel C++

  • Multicore Programming

  • Working with Devices

  • Going Distributed

  • Performance Evalution