GPUs are useful resources for compute-intensive and highly parallelizable operations tasks such as streaming and parallel computing. However, inefficient resource management generates heavy expenses. Yaron Haviv will explain how to fragments applications to microservices and scale GPUs in and out with serverless for maximum resource efficiency. Instead of wasting costs on every data scientist having his own GPU, 10 data scientists can share 3-4 GPUs and use them as needed. He will demonstrate how to improve GPU utilization and sharing, resulting in almost four times faster application performance when compared to the use of GPUs within monolithic architectures. Participants will learn how serverless platforms can fifty times faster when offering GPU support.
