Groq LPU
HoldPlatforms
A latency-focused inference accelerator architecture for large language models and other AI workloads.
Why it's here
Placed in Hold: 1 article(s) of evidence from 1 source(s), led by research-stage coverage, with 0 in the last 30 days. Confidence 24%. Low accumulated evidence, so it defaults conservatively pending more signal.
Evidence (1)
- 7Hacker News·8/23/2026researchSurvey of AI Chip Architectures
This article reviews the rise of domain-specific AI chip architectures in response to the memory wall and the limits of Moore’s Law. It compares deployment approaches such as GPUs, TPU-style systolic accelerators, wafer-scale engines, and low-latency inference chips, focusing on how they move data and scale for training and inference.