See How GPUs are Accelerating Analytics for Finance
Please join Hanweck Associates, Kinetica, and NVIDIA to learn more about how financial services companies are using Machine Learning and accelerated analytics with DGX-1 and GPUs to capitalize on big data in real time.
- Gerald Hanweck, CEO and Co-founder of Hanweck, will kick off the webinar and discuss:
- The emergence and impact of Machine Learning and distributed computing within quantitative finance
- Portfolio stress testing – objectives and challenges to performing rapid on-demand aggregations on large scale datasets
- Eric Mizell, VP of Global Solution Engineering at Kinetica, and Charie Boyle, Senior Director of Product Management at NVIDIA, together will showcase customers use cases for:
- Driving better trading decisions by marrying common financial data sources with external sources – and by applying ML/deep learning algorithms
- Detecting fraud with faster end-to-end performance and the ability to perform aggregate queries and mathematical calculations on-demand
- Interactively managing risk and exposure with ad-hoc analysis on large volumes and disparate types of data, using GPUs to enable real-time data analytics.
Kinetica and NVIDIA have partnered together to provide enterprises the fastest and most scalable GPU-accelerated, in-memory database solution that’s used to solve real-world business and analytics problems. The unique multi-core architecture of GPUs makes it possible to process many computations efficiently and quickly. Ideal for financial services streaming datasets, Kinetica and NVIDIA deliver high-speed data ingest and real-time data analytics.