A Study of Long-Term Architectural Limits to Computing: Galileo

计算的长期架构限制的研究：伽利略

• 批准号: 9509589
• 负责人: James Goodman
• 金额: $ 26.59万
• 依托单位: University of Wisconsin-Madison
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1995
• 资助国家: 美国
• 起止时间: 1995-09-01 至 1998-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9509589&HistoricalAwards=false
• 关键词: Study; Long; Term; Architectural; Limits

Galileo is an investigation into the implications of long range technology advances across the computer field. While projections of narrow scope are difficult and risky because of the rapid progress over a very broad range of technology, it is possible to extrapolate current trends and make intelligent guesses about future computer building blocks. Extrapolating current rates of progress to as little as a decade hence suggesting that incredibly powerful computer systems might not be only possible, but even affordable. Current technology trends will undoubtedly be affected by new discoveries and by limitations long before such performance levels are reached. It is the goal of this research to identify those development directions that are likely to come into conflict or otherwise be retarded, and to investigate the implications of these effects. Future machines will undoubtedly much lower costs of all operations, but some operations will become much cheaper than others. A major goal is to identify the relative improvements on different kinds of operations, and to understand how these changes will affect architecture, the programming environment, and the algorithms used. The processor has long been the heart of a computer system, and though much has been written about other limitations, the CPU still plays a central role in today's architectures. Increasingly the processor is becoming less effective, limited not by its peak processing power, but by the ability of the system to provide work to keep it busy. While processing power is rapidly becoming cheaper, the effective use of memory and communication is becoming the critical challenge in achieving higher performance. Memory costs have declined rapidly and steadily for more than twenty years, and will continue to decline in cost per bit. Access time has not improved dramatically, however, and high-bandwidth, low latency-memory will always be relatively expensive. Limitations in memory access tile and bandwidth are already posing difficult design challenges, and this will only be aggravated by technology trends. This research is investigating how a system can get higher performance form its memory system by applying cheap processing power wherever it can be used effectively. In some sense, the system becomes a collection of memory modules with processing power distributed in ways to maximize the effective use of memory by minimizing communications between memory modules. Memory access time and memory latency are intimately related. Both are critical for a high-performance system, and either can be optimized at the expense of the other. Today memory latency seems to be the more urgent problem, and much current research is devoted to reducing or tolerating memory latency. Assuming that some of these techniques are successful, the more fundamental problem of memory bandwidth emerges. While it may be possible to build systems of arbitrarily high bandwidth, it appears that one of the most important emerging challenges is to make the most effective use of whatever bandwidth is available between modules. By today's standards, future systems will have enormous processing power, huge amounts of memory, and incredible communications bandwidth. Computer systems will be limited by memory modules of insufficient capacity and communication paths of limited bandwidth, with processor distributed generously wherever needed to optimize the effectiveness of memory and communication bandwidth. Galileo is investigating how the architecture of such systems should differ from systems of today. Galileo is investigating how the architecture of such systems should differ from systems of today, and how such systems should be programmed.

伽利略是一个调查的影响，远程技术的进步，整个计算机领域。 虽然由于非常广泛的技术的快速进步，狭隘范围的预测是困难且有风险的，但可以推断当前的趋势并对未来的计算机构建模块做出智能猜测。 将目前的进展速度外推到十年之内，这表明令人难以置信的强大计算机系统不仅是可能的，甚至是负担得起的。 毫无疑问，在达到这样的性能水平之前，当前的技术趋势将受到新发现和局限性的影响。 本研究的目的是确定那些可能发生冲突或以其他方式被推迟的发展方向，并调查这些影响的影响。 未来的机器无疑将大大降低所有操作的成本，但某些操作将比其他操作便宜得多。 一个主要目标是确定不同类型操作的相对改进，并了解这些更改将如何影响架构，编程环境和所使用的算法。 处理器长期以来一直是计算机系统的核心，尽管已经有很多关于其他限制的文章，但CPU仍然在当今的体系结构中发挥着核心作用。 越来越多的处理器变得不那么有效，限制不是它的峰值处理能力，而是由系统提供工作的能力，以保持它忙碌。 虽然处理能力正在迅速变得更便宜，但有效使用内存和通信正在成为实现更高性能的关键挑战。 存储器成本已经快速稳定地下降了20多年，并且每比特的成本将继续下降。 然而，访问时间并没有显著改善，高带宽、低延迟的内存总是相对昂贵的。 存储器访问瓦片和带宽的限制已经构成了困难的设计挑战，并且这只会因技术趋势而加剧。 本研究旨在探讨系统如何在其内存系统中获得更高的性能，并在任何可以有效使用的地方应用廉价的处理能力。 在某种意义上，系统变成了存储器模块的集合，其中处理能力以通过最小化存储器模块之间的通信来最大化存储器的有效使用的方式分布。 内存访问时间和内存延迟是密切相关的。 这两者对于高性能系统都是至关重要的，并且可以以牺牲另一个为代价进行优化。 今天，记忆延迟似乎是更紧迫的问题，目前的许多研究都致力于减少或容忍记忆延迟。 假设这些技术中的一些是成功的，那么更基本的内存带宽问题就出现了。 虽然可以构建任意高带宽的系统，但似乎最重要的新挑战之一是最有效地利用模块之间可用的任何带宽。 按照今天的标准，未来的系统将拥有巨大的处理能力、大量的内存和令人难以置信的通信带宽。 计算机系统将受到容量不足的存储器模块和有限带宽的通信路径的限制，处理器被慷慨地分布在需要优化存储器和通信带宽的有效性的任何地方。 伽利略正在研究这种系统的架构应该如何不同于今天的系统。 伽利略正在研究这种系统的结构应该如何不同于今天的系统，以及这种系统应该如何编程。