论文标题
下一代计算的机会和挑战
Opportunities and Challenges for Next Generation Computing
论文作者
论文摘要
从商业和农业到沟通和娱乐,计算几乎改变了我们生活的各个方面。作为一个国家,我们依靠计算能源,运输和防御系统的设计;并计算燃料的科学发现,这些发现将改善我们对世界的基本理解,并帮助开发解决健康和环境的主要挑战的解决方案。计算已经改变了我们的世界,部分原因是我们的创新可以在过去几十年中的性能和成本表现的计算机上进行一百万倍。背后的推动力是每芯片的晶体管一再倍增,被称为摩尔定律。一个伴随的推动器是丹纳德(Dennard)的缩放率,它使这些性能加倍以大致恒定的力量持续,但是,正如我们将看到的那样,这两种趋势都面临着挑战。考虑一下,在过去30年中,这两种趋势的影响。 1980年代的超级计算机(例如,Cray 2)的额定值近2 gflops,并消耗了近200千瓦的功率。当时,它用于从天气预报到核武器研究的高性能和国家规模的应用。一台类似性能的计算机现在适合我们的口袋,并且消耗少于10瓦。在接下来的30年中,类似的计算/功率降低的含义是什么?也就是说,乘坐Petaflop尺度机器(例如,Cray XK7需要约500 kW的1 pflop(= 1015个操作/sec)的性能)并重复该过程?这样的计算机在您的口袋里有什么可能?它将如何改变高容量计算的景观?在本文的其余部分中,我们阐明了个人到国家规模计算的巨大绩效改进的一些机会和挑战,并讨论了在此规模上实现计算的一些“开箱即用”的可能性。
Computing has dramatically changed nearly every aspect of our lives, from business and agriculture to communication and entertainment. As a nation, we rely on computing in the design of systems for energy, transportation and defense; and computing fuels scientific discoveries that will improve our fundamental understanding of the world and help develop solutions to major challenges in health and the environment. Computing has changed our world, in part, because our innovations can run on computers whose performance and cost-performance has improved a million-fold over the last few decades. A driving force behind this has been a repeated doubling of the transistors per chip, dubbed Moore's Law. A concomitant enabler has been Dennard Scaling that has permitted these performance doublings at roughly constant power, but, as we will see, both trends face challenges. Consider for a moment the impact of these two trends over the past 30 years. A 1980's supercomputer (e.g. a Cray 2) was rated at nearly 2 Gflops and consumed nearly 200 KW of power. At the time, it was used for high performance and national-scale applications ranging from weather forecasting to nuclear weapons research. A computer of similar performance now fits in our pocket and consumes less than 10 watts. What would be the implications of a similar computing/power reduction over the next 30 years - that is, taking a petaflop-scale machine (e.g. the Cray XK7 which requires about 500 KW for 1 Pflop (=1015 operations/sec) performance) and repeating that process? What is possible with such a computer in your pocket? How would it change the landscape of high capacity computing? In the remainder of this paper, we articulate some opportunities and challenges for dramatic performance improvements of both personal to national scale computing, and discuss some "out of the box" possibilities for achieving computing at this scale.