Agentic AI workflows expose CPU-GPU bottlenecks in current enterprise server infrastructure, Microsoft and UT researchers find
Research from Microsoft Azure and University of Texas reveals that multi-step AI workflows create performance bottlenecks between CPUs and GPUs that conventional inference infrastructure cannot handle efficiently, potentially requiring enterprise AI server redesign.
