VQV Signal
NOVA addresses challenges in near-memory processing architectures for hybrid LLMs combining GQA, SSM, and MoE layers. It highlights the technology scaling limits of DRAM cells at 10nm nodes impacting memory performance.
NOVA addresses challenges in near-memory processing architectures for hybrid LLMs combining GQA, SSM, and MoE layers. It highlights the technology scaling limits of DRAM cells at 10nm nodes impacting memory performance.
AI-assisted summary based on the listed source.
The rapid evolution of hybrid large language models (LLMs), which interleave grouped-query-attention (GQA), state-space model (SSM), and Mixture-of-Experts (MoE) layers, introduces two fundamental challenges for near-memory processing (NMP) architectures. First, the Technology Wall: the conventional 6F^2 DRAM cell...
As hybrid LLMs evolve, overcoming memory and processing bottlenecks is critical for efficient inference. NOVA's co-design approach targets these hardware constraints to better support complex LLM workloads.
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