In the 1980s, Mead and Conway democratized chip design, and high-level language programming surpassed assembly language programming, which made instruction set advances viable. Innovations like reduced instruction set computers (RISCs), superscalar, and speculation ushered in a golden age of computer architecture, when performance doubled every 18 months. Unfortunately, this golden age has ended: microprocessor performance improved only 3% last year.
The ending of Dennard scaling and Moore’s law and the deceleration of performance gains for standard microprocessors are not problems that must be solved but facts that if accepted, offer breathtaking opportunities. The good news is that our ravenous ML colleagues want the fastest computers that we can build; ML researchers at the forefront increase their computation appetite for training by 10x per year.
High-level, domain-specific languages and architectures and freeing architects from the chains of proprietary instruction sets will usher in a new golden age. David Patterson explains why, despite the end of Moore’s law, he expects an outpouring of codesigned ML-specific chips and supercomputers that will improve even faster than Moore’s original 1965 prediction. Like the 1980s, the next decade will be exciting for computer architects in academia and industry alike.
David Patterson is a professor emeritus at UC Berkeley, a distinguished engineer at Google Brain, and vice chair of the board of the RISC-V Foundation. His most successful research projects are reduced instruction set computers (RISC), redundant arrays of inexpensive disks (RAID), and network of workstations, which together led to multibillion-dollar industries, seven books, and about 40 honors, including election to the National Academy of Engineering, the National Academy of Sciences, and the Silicon Valley Engineering Hall of Fame. He also shared the ACM Turing award, the IEEE von Neumann Medal, and NEC C&C prize with John Hennessy, past president of Stanford University and coauthor of two of his books. David holds an AB, MS, and PhD, all from UCLA.
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