Memory customization is not always a top priority when a design team plans a new system-on-chip (SoC) project. But often it should be. This may not be an obvious statement. Granted, SRAM claims a lot ...

Abstract: A novel chip stacking method with low thermal resistance for 3-D integration of a large number of memory chips and processor chips is proposed, namely massive orthogonal stacking assembly of ...

Memory is the premier determiner of who we are and how we think. As Samuel Johnson put it in 1759, “Memory is the primary and fundamental power without which there could be no other intellectual ...

The news that Nvidia's (NVDA) Vera Rubin GPU line has had a design change to 2-die from 4-die is likely the reason memory stocks fell sharply on Monday, GF Securities said. “In our view, due to the ...

Google said this week that its research on a new compression method could reduce the amount of memory required to run large language models by six times. SK Hynix, Samsung and Micron shares fell as ...

Running a 70-billion-parameter large language model for 512 concurrent users can consume 512 GB of cache memory alone, nearly four times the memory needed for the model weights themselves. Google on ...

If Google’s AI researchers had a sense of humor, they would have called TurboQuant, the new, ultra-efficient AI memory compression algorithm announced Tuesday, “Pied Piper” — or, at least that’s what ...

Even if you don’t know much about the inner workings of generative AI models, you probably know they need a lot of memory. Hence, it is currently almost impossible to buy a measly stick of RAM without ...

Nvidia researchers have introduced a new technique that dramatically reduces how much memory large language models need to track conversation history — by as much as 20x — without modifying the model ...

Enterprise AI applications that handle large documents or long-horizon tasks face a severe memory bottleneck. As the context grows longer, so does the KV cache, the area where the model’s working ...