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 ...

DeepSeek’s conditional memory fixes silent LLM waste: GPU cycles lost to static lookups

Through systematic experiments DeepSeek found the optimal balance between computation and memory with 75% of sparse model ...
The Register on MSN

Raspberry Pi 5 gets LLM smarts with AI HAT+ 2

TOPS of inference grunt, 8 GB onboard memory, and the nagging question: who exactly needs this? Raspberry Pi has launched the AI HAT+ 2 with 8 GB of onboard RAM and the Hailo-10H neural network ...
Semiconductor Engineering

Pooling CPU Memory for LLM Inference With Lower Latency and Higher Throughput (UC Berkeley)

“The rapid growth of LLMs has revolutionized natural language processing and AI analysis, but their increasing size and memory demands present significant challenges. A common solution is to spill ...
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 ...
Forbes

NVIDIA L40S: A Datacenter GPU For Omniverse And Graphics That Can Also Accelerate AI Training & Inference

I’m getting a lot of inquiries from investors about the potential for this new GPU and for good reasons; it is fast! NVIDIA announced a new passively-cooled GPU at SIGGRAPH, the PCIe-based L40S, and ...