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Nagare Labs推进Z2RAM存算一体原型

AI 总结

Nagare Labs称,Z2RAM可将以DRAM密度、SRAM速度的存储直接置于AI加速器上,以应对HBM堆叠面临的带宽、良率和散热难题。创始人论文显示,三晶体管单元在85°C下可保持数据超过300秒,但Gen 1所称5倍SRAM密度、14倍DRAM速度等指标仍是厂商预测。该技术目前仍处于实验室原型阶段,尚未拥有晶圆厂,也没有已发表单元展示95°C以上的保持能力。

深度见解

Z2RAM为AI加速器提供了一种存算一体路线,但核心性能尚未在晶圆厂制造的多层堆叠中验证。

A Pat Gelsinger-backed Georgia Tech spinout, Nagare Labs, says its Z2RAM can put SRAM-speed memory, at DRAM density, directly on top of AI chips. The founders’ own papers show a fast-improving cell that, tested up to 85 degrees Celsius, holds data for over 300 seconds. Gen 1 is projected to have 5x SRAM density with six stacked layers, 14x DRAM speed, and 3x less read energy than SRAM.

AI chips require a lot of bandwidth, and it has been challenging to get sufficient yields of high-bandwidth memory (HBM) to feed them. Even when manufacturers can get it, some reportedly plan to settle for fewer layers for yield reasons, and heat is another. Heat is also why Samsung’s zHBM, which stacks DRAM directly on the processor, is planned at only about four layers.

Alternatives include high-bandwidth flash, still in development, which stacks NAND like HBM and would sit beside the GPU, or SRAM stacked directly on the die, which is less dense and more expensive for the capacity, but also faster. DRAM, which is more capacious, can sit on top of the compute, but heat limits how hard the logic underneath can run.

#Nagare Labs#Z2RAM#Georgia Tech#HBM#Samsung zHBM#Micron vHBM#AMD 3D V-Cache

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