Seminar Overview
In this seminar, participants will gain practical insights into improving AI workload performance and reducing infrastructure costs through performance engineering. Featuring real-world examples and case studies using Fixstars AIBooster, attendees will learn GPU profiling techniques, job-based performance tracking, and effective methods for identifying and resolving performance bottlenecks. Ideal for technical leaders and infrastructure managers, this session will empower participants to maximize their AI investments.
Speaker
Ryan is a software engineer at Fixstars Solutions specializing in high-performance C++ programming. His work includes building high-throughput, GPU-accelerated image processing pipelines; designing optimization algorithms inspired by quantum annealing; and enhancing computational lithography workflows.
He holds a master’s degree in computer science from Tufts University, a master’s in physics from the California Institute of Technology, and bachelor’s degrees in physics and mathematics from the University of Rochester.
Agenda
- What is AI Performance Engineering?
- Core Features and Advantages of Fixstars AIBooster
- GPU Profiling Methods and Applications
- Practical Optimization Techniques for AI Workloads
- Q&A Session
Total 50 minutes
* You can enter and leave the session at any time.
* Please note that the schedule and content may change without prior notice.
AIBooster is a performance engineering platform for continuously observing and improving the performance of AI workloads.
Through comprehensive dashboards, users can visualize the utilization efficiency of various hardware resources—including CPU, GPU, interconnect, and storage—as well as identify software bottlenecks to analyze AI workload performance characteristics. Furthermore, by applying optimization frameworks specifically designed for AI workloads, users can achieve efficient performance improvements.
Date and time
Thursday, August 14, 2025
12:00 PM - 12:50 PM PDT
2:00 PM - 2:50 PM CDT
3:00 PM - 3:50 PM EDT
Location
Zoom
Target Audience
- AI Infrastructure Managers and Engineers
- Technical Leaders of AI Development Teams
- Project Managers aiming for cost-efficient AI projects
- Data Scientists and Researchers interested in performance engineering
Participation fee
Free
