Presented By O’Reilly and Cloudera
Make Data Work
September 11, 2018: Training & Tutorials
September 12–13, 2018: Keynotes & Sessions
New York, NY
Onur Yilmaz

Onur Yilmaz
Deep Learning Solution Architect, NVIDIA

Onur Yilmaz is a deep learning solution architect at NVIDIA, where he works on deep learning use cases for finance and helps researchers and data scientists adopt deep learning and GPU technology. Onur holds a PhD in computer engineering from the New Jersey Institute of Technology; his dissertation focused on traditional machine learning and high-performance signal processing for finance.

Sessions

5:25pm–6:05pm Wednesday, 09/12/2018
Accelerating financial data science workflows with GPUs
Location: 1A 15/16 Level: Intermediate
Secondary topics:  Financial Services
Joshua Patterson (NVIDIA), Onur Yilmaz (NVIDIA)
GPUs have allowed financial firms to accelerate their computationally demanding workloads. Today, the bottleneck has moved completely to ETL. The GPU Open Analytics Initiative (GoAi) is helping accelerate ETL while keeping the entire workflow on GPUs. Joshua Patterson and Onur Yilmaz discuss several GPU-accelerated data science tools and libraries. Read more.