Module 1: Introduction to Performance, Portability, and Productivity for HPC

Rakshith Krishnappa, Developer Evangelist at Intel
Webinar Beginner
ALP Module 1

In this session, we will introduce you to Data Parallel C++ and the importance of performance, portability, and productivity for HPC development. We will set up a Jupyter Lab environment for training, which will allow hands-on compilation and execution of simple DPC++ code samples.


  • Introduction to Data Parallel C++ (10min)
  • Importance of Performance, Portability, and Productivity (10min)
  • Setup Jupyter Lab environment for training and hands-on execution of code samples (30min)
  • Code walk-thru of matrix multiplication implementation using Math Kernel Library (15min)
  • Compile and Execute the same matrix multiplication code sample on CPU and GPU offload (15min)

This module is a part of the Aurora Learning Paths Series.


Rakshith Krishnappa is a developer evangelist at Intel, focused on oneAPI, DPC++, and High-Performance Computing. For the last 16 years, he has worked on various Intel products including CPUs, Graphics, GPUs, HPC products, and Software solutions.