Researchers from Micron Technology and Argonne National Laboratory have released “Understanding Inference Scaling for LLMs: Bottlenecks, Trade-offs, and Performance Principles”. Abstract “The transition from standard generative AI to reasoning-centric architectures, exemplified by models capable of extensive Chain-of-Thought (CoT) processing, marks a fundamental paradigm shift in system requirements. Unlike traditional workloads dominated by compute-bound prefill, reasoning... » read more The post Characterization of GPU-based Inference for Reasoning-Centric LLMs (Micron, Argonne) appeared fir
Source: Semiconductor Engineering — read the full report at the original publisher.