[Webinar] Speed Up Your AI: Practical Performance Engineering Tips

🚀 Speed Up Your AI — Practical Performance Engineering from the Field

In this live session, Fixstars engineers will explore AI performance engineering from a systems perspective—demonstrating how to detect and eliminate inefficiencies across GPU, CPU, memory, and interconnect layers in both training and inference pipelines. Participants will learn how to conduct low-level hardware profiling, interpret utilization metrics, and apply kernel-level and I/O optimizations that translate directly into measurable improvements in throughput, latency, and cost efficiency.

Through real-world case studies and a guided demonstration of Fixstars AIBooster, you’ll see how engineers are achieving:

• Up to 5× faster training on large-scale models
• 50% lower inference costs through targeted tuning
• Sustainable ROI gains using systematic performance engineering

Who Should Watch

• Infrastructure and platform engineers managing AI workloads
• ML engineers and DevOps optimizing GPU clusters
• CTOs, tech leads, and system architects seeking compute efficiency
• Anyone building or scaling AI infrastructure with performance in mind

Whether you’re optimizing LLMs, computer vision models, or multi-node training pipelines, this session delivers actionable techniques and data-backed methods to help you make AI systems faster, leaner, and more cost-efficient.