A Nature paper describes an innovative analog in-memory computing (IMC) architecture tailored for the attention mechanism in large language models (LLMs). They want to drastically reduce latency and ...
Content Addressable Memory (CAM) architectures provide a powerful approach to high-speed data searches by comparing search data against an entire memory in parallel, rather than relying on sequential ...
The growing imbalance between the amount of data that needs to be processed to train large language models (LLMs) and the inability to move that data back and forth fast enough between memories and ...
For decades, compute architectures have relied on dynamic random-access memory (DRAM) as their main memory, providing temporary storage from which processing units retrieve data and program code. The ...
AI workloads need to position more memory that uses less power in ever-closer proximity to computational logic. That overriding imperative is driving new memory designs and new materials exploration ...
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