Eddie
I am a data scientist with a background in applied math, and experience working in a variety of customer-facing and R&D roles. Over the last six years I have worked at startups and at Intel helping customers and open-source communities use machine learning software.
Sessions
High performance computing has been a key tool for computational researchers for decades. More recently, cloud economics and the intense demand for running AI workloads has led to a convergence of older, established standards like MPI and a desire to run them on modern cloud frameworks like Kubernetes. In this tutorial, we will discuss the historical arc of massively parallel computation, focusing on how modern cloud frameworks like Kubernetes can both serve data scientists looking to build production-grade applications and run HPC-style jobs like MPI programs and distributed AI training. Moreover, we will show practical examples of submitting these jobs in a few lines of Python code.