The evolution of DDR5 and DDR6 represents a inflexion point in AI system architecture, delivering enhanced memory bandwidth, lower latency, and greater scalability.
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.
Researchers have developed a new type of memory cell that can both store information and do high-speed, high-efficiency calculations. The memory cell enables users to run high-speed computations ...
Content Addressable Memory (CAM) is an advanced memory architecture that performs parallel search operations by comparing input data against all stored entries simultaneously, rather than accessing ...
TL;DR: Micron is sampling its new 192GB SOCAMM2 memory module, featuring advanced 1-gamma DRAM technology for over 20% improved power efficiency. Designed for AI data centers, SOCAMM2 offers high ...
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MIT's chip stacking breakthrough could cut energy use in power-hungry AI processes
Data doesn’t have to travel as far or waste as much energy when the memory and logic components are closer together.
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