How Fast Do Algorithms Improve? [Point of View]

• Published in: Proceedings of the IEEE Vol. 109; no. 11; pp. 1768 - 1777
• Main Authors: Sherry, Yash, Thompson, Neil C.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.11.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Approximation algorithms; Clustering algorithms; Complexity theory; Microprocessors; Prediction algorithms; Problem solving; Scientists; Solvers; Time complexity
• ISSN: 0018-9219; 1558-2256; 1558-2256
• DOI: 10.1109/JPROC.2021.3107219

Algorithms determine which calculations computers use to solve problems and are one of the central pillars of computer science. As algorithms improve, they enable scientists to tackle larger problems and explore new domains and new scientific techniques <xref ref-type="bibr" rid="ref1">[1] , <xref ref-type="bibr" rid="ref2">[2] . Bold claims have been made about the pace of algorithmic progress. For example, the President's Council of Advisors on Science and Technology (PCAST), a body of senior scientists that advise the U.S. President, wrote in 2010 that "in many areas, performance gains due to improvements in algorithms have vastly exceeded even the dramatic performance gains due to increased processor speed" <xref ref-type="bibr" rid="ref3">[3] . However, this conclusion was supported based on data from progress in linear solvers <xref ref-type="bibr" rid="ref4">[4] , which is just a single example. With no guarantee that linear solvers are representative of algorithms in general, it is unclear how broadly conclusions, such as PCAST's, should be interpreted. Is progress faster in most algorithms? Just some? How much on average?