interview

Queue editorial board member Bryan Cantrill. Cantrill is best known for developing DTrace, a tool for dynamic instrumentation of production systems that helps companies identify and fix performance bottlenecks. Whitney was gracious enough to invite Cantrill to his home in Palo Alto, where they spoke about his career, his languages, and the essence of elegance.

 

BRYAN CANTRILL You are a bit of a rarity in software engineering in that you have been writing software on a daily basis for decades. Your first introduction to computing was APL with the master, Ken Iverson. What was that like?

ARTHUR WHITNEY In 1969, I was 11, and Ken Iverson was at IBM Research in Yorktown. He had been a friend of my dad’s at Harvard in the ’40s. We lived in Alberta, but we were driving around the continent and went to visit him. He showed me programming on a terminal in his house in Mount Kisco. This was in the ’60s, and already it was interactive, and it was very quick to write programs and get results.

BC You must have been the only 11-year-old on the planet getting that kind of demonstration of programming in 1969.

AW Of course, I had no idea about that, and I didn’t really pay much attention. He showed me some stuff, and I thought it was cool. In ’ 74 when I went to a university and took a computer class, they were using punch cards, which made no sense because five years earlier I had already seen interactive programming.

BC Did you start working on APL at Waterloo?

AW No, at Waterloo I just did some APL for a week. I was a math major and I wasn’t interested in computers because I just wanted to do pure math. So I really missed a big opportunity.

BC Well, I’m not sure if you missed it or if you just found the opportunity a different way.

AW It took me a long time. For the next 10 years I did a little bit of APL in the summers as a consultant, but it wasn’t until about 1980 when I was working with Ken at a Canadian company called I.P. Sharp that I really began using it regularly. Ken had retired from IBM after 20 years and was working at I.P. Sharp in Toronto.

I.P. Sharp was an amazing company. It had its own worldwide network that had nothing to do with DARPA (Defense Advanced Research Projects Agency). We were sending e-mails and instant messages to Australia and Singapore. The whole company was APL. BC They were selling APL time sharing, right?

AW Yes, and it was easy because the one computer in Toronto was running the entire world.

BC What kinds of problems were people using the APL time-sharing service for?

AW It was mostly general-purpose business computing, such as accounting systems. I did a 2-billion-row database, so we were doing very big databases and data analysis—what today, 20 years later, they call OLAP (online analytical processing).

I left I.P. Sharp sometime around 1980. Then I went to graduate school at the University of Toronto where I did pure mathematics, but mostly I was just goofing around. All through the ’80s I was implementing my own languages: object-oriented languages, a lot of different LISPs, Prolog. In 1985 I got a job at Stanford, where I implemented a Prolog inference-engine kind of language. Then I was with an artificial intelligence company called Teknowledge. BC Were you developing these languages because you needed a certain expressive power in the language to solve a particular problem at hand? What were the motivations for these languages? AW My motivation was always to create a general-purpose programming language that would solve all problems and be interpreted, but fast.

At Stanford the language was determined by the professor, and he wanted to have an inference engine, so the motivation there was artificial intelligence, but I wasn’t much interested in that.

My big break was in 1988 when I joined Morgan Stanley. There the motivation was a terabyte of TIC (Treasury International Capital) data, and back then there were a few million transactions a day being processed by realtime trading systems. I think we had one of the biggest trading operations in the world. We had a portfolio that was a billion dollars: half a billion long, half a billion short. We were trading every second electronically. The data set was a terabyte, but we compressed it down. It was pairs trading, and I wrote an APL to do all of that—the big database and the realtime trading—so our entire department was using my language. BC You had used APL, and then you explored these other languages—Prolog variants and so on—but when you got to Morgan Stanley you came back to APL. What brought you back? AW I much preferred implementing and coding in LISP, but once I was dealing with big data sets and then having to do fairly simple calculations, APL just seemed to have the better vocabulary.