07-12, 17:45–18:40 (US/Pacific), Room 317
If you have interest in NumPy, SciPy, Signal Processing, Simulation, DataFrames, or Graph Analysis, we'd love to hear what performance you're seeing and how you're measuring. We've been working to accelerate your favorite packages on GPUs
Senior Math Libraries Engineer @NVIDIA
Adam Thompson is a Principal Technical Product Manager at NVIDIA where he focuses on building hardware and software platforms targeting real-time AI, smart sensors, and tying high speed sensor I/O to GPU-accelerated compute. His work advances edge and datacenter/cloud collaborative workloads that integrate Digital Twins of instruments and AI training/fine-tuning deployments.
Adam is also the creator of cuSignal – a GPU-accelerated signal processing library written in Python. With over 400,000 downloads, cuSignal is widely used in the sensor processing communities, and - as of CuPy v13, is fully integrated within CuPy library.
He holds a Masters degree in Electrical and Computer Engineering from Georgia Tech and a Bachelors Degree in Electrical Engineering from Clemson University.
In his free time, Adam enjoys baking, listening to (and discovering!) indie music, modern lit, pour-over coffee techniques, and teaching.
Eric is a research scientist at NVIDIA where he develops the open-source Python library Warp. His research interests lie in the intersection of simulation and robotics, particularly differentiable simulators that can be used to reduce the reality gap and control dynamical systems through optimization.
He received his Ph.D. in Computer Science from the University of Southern California under the supervision of Prof. Gaurav Sukhatme.
