Google researchers have revealed that memory and interconnect are the primary bottlenecks for LLM inference, not compute power, as memory bandwidth lags 4.7x behind.
A new technical paper titled “Memory-Centric Computing: Recent Advances in Processing-in-DRAM” was published by researchers at ETH Zurich. “Memory-centric computing aims to enable computation ...
Rapid advancements in AI are becoming commonplace, driven by large language models (LLMs) that now exceed 1 trillion parameters. While these AI models are revolutionizing many industries, their ...
The rapid advancement of artificial intelligence (AI) is driving unprecedented demand for high-performance memory solutions. AI-driven applications are fueling significant year-over-year growth in ...
Agentic AI is driving a major transformation in computing, enabled by more powerful processors and new semiconductor manufacturing techniques. Traditional single-chip architectures are reticle-limited ...
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