NextBigFuture

Defeating Nondeterminism in LLM Inference by Thinking Machines

A research article by Horace He and the Thinking Machines Lab (X-OpenAI CTO Mira Murati founded) addresses a long-standing issue in large language models (LLMs). Even with greedy decoding bu setting ...
VentureBeat

How attention offloading reduces the costs of LLM inference at scale

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Rearranging the computations and hardware used to serve large language ...
Semiconductor Engineering

LLM Inference On CPUs (Intel)

“Large language models (LLMs) have demonstrated remarkable performance and tremendous potential across a wide range of tasks. However, deploying these models has been challenging due to the ...
Semiconductor Engineering

LLM Inference: Core Bottlenecks Imposed By Memory, Compute Capacity, Synchronization Overheads (NVIDIA)

A new technical paper titled “Efficient LLM Inference: Bandwidth, Compute, Synchronization, and Capacity are all you need” was published by NVIDIA. “This paper presents a limit study of ...