Today across our customer base we are witnessing AI becoming part of so many applications and workflows. AI technologies are playing an increasingly important role in traditional HPC modeling and simulation applications. At the same time, AI applications are getting large enough that they require HPC technologies. There's a large and growing demand for deep learning training as more businesses look for ways to leverage ever more data in their applications. Models are getting bigger and more complex in the drive to improve their accuracy and usefulness.

At this week's Intel HPC Developer Conference in Denver, Colrado, USA this week, Raja Koduri, senior vice president, chief architect, and general manager of architecture, graphics and software at Intel (pictured), introduced a new category of discrete general-purpose GPUs optimised for artificial intelligence (AI) and high performance computing (HPC) convergence. The Ponte Vecchio general purpose GPU is based on the Xe architecture. "HPC and AI workloads demand diverse architectures, ranging from CPUs, general-purpose GPUs and FPGAs, to more specialised deep-learning neural network processors (NNPs), which Intel demonstrated earlier this month," said Koduri. Ponte Vecchio is architected for HPC modeling and simulation workloads and AI training. It will be manufactured on Intel's 7nm technology and will be Intel's first Xe-based GPU optimised for HPC and AI workloads.