SDxCentral

AI inference crisis: Google engineers on why network latency and memory trump compute

Researchers propose low-latency topologies and processing-in-network as memory and interconnect bottlenecks threaten inference economic viability ...
Semiconductor Engineering

LLM Inference on GPUs (Intel)

“Transformer based Large Language Models (LLMs) have been widely used in many fields, and the efficiency of LLM inference becomes hot topic in real applications. However, LLMs are usually ...
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 ...
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 ...
NextBigFuture

OpenAI Strawberry LLM Reasoning Needs More Compute and Energy for Inference

Jim Fan is one of Nvidia’s senior AI researchers. The shift could be about many orders of magnitude more compute and energy needed for inference that can handle the improved reasoning in the OpenAI ...
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 ...