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[交流] 文章推荐:极限尺寸计算机体系结构(Extreme-scale computer architecture)

文章链接(开放获取): https://doi.org/10.1093/nsr/nwv085

计算机晶体管的尺寸不断减小,对于芯片集成化的要求越来越高。“极限尺寸计算机体系结构(Extreme-scale computer architecture)”的概念应运而生,极限尺寸计算机体系结构设计的核心是能量效率(energy efficiency)的提高。在《国家科学评论》(National Science Review)的这篇perspective文章中,作者Josep Torrellas对这一领域面临的挑战和解决方法进行了详细介绍。

Introduction
As transistor sizes continue to scale down, we are about to witness extraordinary levels of chip integration. Sometime early in the next decade, as we reach 7 nm, we will be able to integrate, for example, 1000 sizable cores and substantial memory on a single die. There are many unknowns as to how to build a general-purpose architecture in such an environment. However, we know that the main challenge will be to make it highly energy efficient. Energy and power consumption have emerged as the main obstacles to designing more capable architectures.

Given this energy efficiency challenge, researchers have coined the term ‘Extreme Scale Computer Architecture’ to refer to computer organizations that, loosely speaking, are 100–1000 times more capable than current systems for the same power consumption and physical footprint. For example, these organizations should deliver a datacenter that provides exascale performance (10^18 operations per second) for 20 MW, a departmental server that provides petascale performance (10^15 operations per second) for 20 KW, and a portable device that provides sustained terascale performance (10^12 operations per second) for 20 W. Extreme-scale computing is concerned with technologies that are applicable to all machine sizes—not just high-end systems.

Extreme-scale computer architectures need to be designed for energy efficiency from the ground up. They need to have efficient support for concurrency, since only massive parallelism will deliver this performance. They should also minimize data transfers—since moving data around is a major source of energy consumption. Finally, they need to leverage new technologies that will be developed in the next few years. These technologies include low supply voltage (Vdd) operation, 3D die stacking, resistive memories, and photonic interconnects.

In this paper, we outline some of challenges that appear at different layers of the computing stack, and some of the techniques that can be used to address them.

《国家科学评论》是中科院主管的英文综述性学术期刊,最新影响因子(2016)为8.843。
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