The Innovation Engine • Government-funded Academic Research

Media: article
Title: The Innovation Engine • Government-funded Academic Research
Author: David Patterson
Review published as: 148112
Edited by: Communications of the ACM

David Patterson needs no introduction. As the brain behind many of the inventions that shaped the computing industry (repeatedly) over the past 40 years, when he put forward an opinion article in Communications of the ACM targeting the current political waves in the US, I knew I had to write this review.

Patterson worked for a a public university (University of California Berkeley) between 1976 and 2016, and in this article he argues how government-funded academic research (GoFAR) allows for faster, more effective, and freer development than private sector-funded research would, putting his own career milestones as an example of how public money that went to his research has easily been amplified by a factor of 10,000:1 for the country’s economy, and 1,000:1 particularly for the government.

Patterson illustrates this by quoting five of the “home-run” research projects he started and pursued with government funding, eventually spinning them off as successful startups:

Reduced Instruction Set Computing (RISC): a microprocessor architecture that reduces the complexity and power consumption of central processing units (CPUs), yielding much smaller and more efficient processors.
Redundant Array of Inexpensive Disks (RAID): Patterson experimented with a way to present a series of independent hard drive units as if they were a single larger one, leading to increases in capacity and reliability beyond what the industry could provide in single drives for a fraction of the price.
A network of workstations (NOW): Introduced what we now know as computer clusters (in contrast to large-scale massively multiprocessed cache-coherent systems known as “supercomputers”), which nowadays power over 80 percent of the TOP500 supercomputer list and are the computer platform of choice at practically all data centers.
The Reliable Adaptive Distributed Systems Lab (RAD Lab) pursued the technology for data centers to be self-healing and self-managing, testing and pushing early cloud scalability limits
The Parallel Computing Lab (ParLab) explores how to improve designs of parallel software and hardware, presenting the ground works that proved that inherently parallel graphics processing units (GPUs) were better than CPUs at machine learning tasks. It also developed the RISC-V open instruction set architecture (ISA).

Patterson identifies the principles for the projects he has led that are specially compatible with the ways research works in universitary systems: multidisciplinary teams, demonstrative usable artifacts, seven- to ten-year impact horizons, five-year sunset clauses (to create urgency and to lower opportunity costs), physical proximity of collaborators, and leadership followed on team success rather than individual recognition.

It could be argued that it’s easy to point at Patterson’s work as a successful example while he is not the average academic. However, the argument he makes on regard to how GoFAR has been fundamental to advances made in science and technology, but also of biology, medicine, and several other fields, is very clear.