内存计算会成为联想处理器的新曙光吗?

Leonid Yavits
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摘要

近年来,计算机体系结构面临着巨大的挑战:在对性能需求不断增长的同时,通用CPU的性能提升几乎停滞不前。原因之一是内存和电源墙,因此数据传输越来越主导计算。通过显著减少数据传输,以数据为中心(或内存中)的计算有望缓解内存和电源墙的问题。联想处理器是20世纪60年代发明的一种非冯·诺依曼计算机,但直到最近才被有效地抛弃。它以一种完美的类似归纳的方式使用联想记忆进行计算,使用联想记忆单元进行数据存储和处理。关联处理器可以使用传统CMOS以及新兴存储器来实现。我们表明,在各种数据密集型工作负载中,关联处理器可以比最先进的计算平台高出近两个数量级。
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Will computing in memory become a new dawn of associative processors?

Computer architecture faces an enormous challenge in recent years: while the demand for performance is constantly growing, the performance improvement of general-purpose CPU has almost stalled. Among the reasons are memory and power walls, due to which data transfer increasingly dominates computing. By significantly reducing data transfer, data-centric (or in-memory) computing promises to alleviate the memory and power walls. Associative processor is a non von Neumann computer invented in the 1960s but effectively cast aside until recently. It computes using associative memory in a perfect induction like fashion, using associative memory cells for both data storage and processing. Associative processor can be implemented using conventional CMOS as well as emerging memories. We show that associative processor can outperform state-of-the-art computing platforms by up to almost two orders of magnitude in a variety of data-intensive workloads.

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