Optimize AI workloads and cut GPU costs with Fixstars.

(Rebroadcast of the October 30 Webinar + Live Q&A Session)

Join us for a special rebroadcast of our October 30 webinar, followed by a live Q&A with Fixstars engineers.

In this session, you’ll explore AI performance engineering from a systems perspective—learning how to detect and eliminate inefficiencies across GPU, CPU, memory, and interconnect layers in both training and inference pipelines.

You’ll gain practical insights into:

• Conducting low-level hardware profiling and interpreting utilization metrics
• Applying kernel-level and I/O optimizations for measurable improvements in throughput, latency, and cost efficiency

Through real-world case studies and a guided demonstration of Fixstars AIBooster, discover how engineers are achieving:

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

Who Should Watch

• Infrastructure and platform engineers managing AI workloads
• ML engineers and DevOps teams are 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, data-backed methods to make your AI systems faster, leaner, and more cost-efficient.

Time: 3:00 pm EST

Free!

Registration