Garth gibson has spent his career pushing data storage systems to higher levels of performance, reliability, and scalability. While he was a graduate student at the University of California, Berkeley, Gibson was a part of groundbreaking research on Redundant Arrays of Inexpensive Disks (RAID). Later, as a professor at Carnegie Mellon University, he worked on projects like Network Attached Secure Disk (NASD) technology, and a clustered storage system used by Roadrunner, the world's first peta-scale supercomputer. Here, he speaks about handling failures, collaborating with industry and academia, and how deep learning has impacted systems design.
When you were a graduate student at the University of California at Berkeley, you joined a computer architecture team led by David Patterson that was building a complete system based on RISC concepts. How did you get started on storage?