Keynote Talk: Algorithm Improvement: How Fast Has It Been and How Much Farther Can It Go?

Neil C. Thompson
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Abstract

In this talk, I report on a large-scale census of algorithm improvement spanning 11 sub-fields of computer science, 57 textbooks and more than 1,100 research papers. Across 113 algorithm problems, we find enormous variation in how fast algorithms have improved. Around half experience little or no improvement. At the other extreme, 13% experience transformative improvements, radically changing how and where they can be used. Overall, we find that, for moderate-sized problems, 30% to 45% of algorithmic problems had improvements comparable or greater than those that users experienced from Moore's Law and other hardware advances. I will also discuss our comparison of the upper bounds and lower bounds for these algorithm problems, where we find that nearly two-thirds are already asymptomatically optimal --- representing a triumph for the field, but also a challenge for future progress.
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主题演讲:算法改进:进展有多快,还能走多远?
在这次演讲中,我报告了一项大规模的算法改进普查,涵盖了计算机科学的11个子领域,57本教科书和1100多篇研究论文。在113个算法问题中,我们发现算法的改进速度存在巨大差异。大约一半的人几乎没有改善。在另一个极端,13%的人经历了变革性的改进,从根本上改变了他们的使用方式和地点。总的来说,我们发现,对于中等规模的问题,30%到45%的算法问题的改进与用户从摩尔定律和其他硬件进步中获得的改进相当或更大。我还将讨论我们对这些算法问题的上界和下界的比较,我们发现近三分之二的算法已经是无症状最优的——这代表了该领域的胜利,但也对未来的进步提出了挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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