Natalia Vassilieva from HP Labs gave this talk at the HPC User Forum in Milwaukee. “Our Deep Learning Cookbook is based on a massive collection of performance results for various deep learning workloads on different hardware/software stacks, and analytical performance models. This combination enables us to estimate the performance of a given workload and to recommend an optimal hardware/software stack for that workload. Additionally, we use the Cookbook to detect bottlenecks in existing hardware and to guide the design of future systems for artificial intelligence and deep learning.”