Hudson River Trading Powering cutting-edge quantitative research models with Google Cloud
AI Summary
In this insightful presentation, Ryan Chsta, a system engineer at Hudson River Trading, discusses the company’s use of Google Cloud infrastructure to enhance its quantitative research models. He highlights the importance of Google Cloud products, particularly GPUs and Hyperdisk, in scaling their machine learning capabilities. Chsta elaborates on the dynamic nature of their workloads and how Google Cloud’s features allow them to efficiently increase their capacity with ease. He shares that the integration of Hyperdisk storage pools has significantly reduced their costs and improved job processing times for internal end users, enabling them to submit jobs for immediate execution rather than waiting for extended periods. Overall, Hudson River Trading’s collaboration with Google Cloud has led to enhanced operational efficiency and substantial cost savings.