As the performance and energy efficiency demands of AI inference continue to rise, SRAM-based architectures have become a critical core in LPU / NPU design.
This webinar will focus on the application of SRAM and the challenges of test and repair within LPU / NPU architectures. We will explore the critical role of SRAM in AI inference systems and share how START™ v5, combined with UDA, TEC, MART, and Flexible Repair, helps design teams achieve the optimal balance between performance, yield, and reliability.
Key Highlights
- Groq LPU Architecture
- Why LPU and NPU require SRAM
- Applications of START™ v5, UDA, TEC, MART, and Flexible Repair