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YOW 2011 Simon Peyton Jones - Closer to Nirvana

jasonofthel33t

11K subscribers • 11 videos on Hallway

YouTube
  • Recommended by 3 people: 3 in engineering communities.
  • A classic. People kept recommending it from 2013 to 2019.
  • Presented by Simon Peyton Jones, researcher at Microsoft Research

Intermediate. Assumes working knowledge.

11K views13 years ago3 recommendations

Programming languagesSystems programmingHaskellConcurrency and parallelismCompilers and interpreters

Simon Peyton Jones discusses the evolution of the Glasgow Haskell Compiler, Software Transactional Memory, and making functional programming practical.

Cross posted from channel9.msdn.com/Blogs/Charles/YOW-2011-Simon-Peyton-Jones-…. Charles: I caught up with Simon Peyton-Jones, author of the Glasgow Haskell Compiler (GHC) and a key contributor to the Haskell functional programming language, at YOW! 2011. Simon is a pure functional guy. That said, he's OK with side effects as long as you can control them (so, monads are great!). Smiley Simon works at Microsoft as a research scientist in MSR. Simon's work on Haskell is legendary and the language has seen an increase in usage over the years and a steady evolution toward being not only a general purpose, strongly-typed functional programming language, but also a practical one. No longer is Haskell suited only for academic experimentation (though this continues to be an important aspect of the language—in fact, it's one of the very effective ways the language is pushed forward). As Simon says, Haskell is like a laboratory in which to test new functional ideas and novel language constructs. One of the very interesting aspects of Haskell is how the surface language (so, the syntax you write) is boiled down to a very small intermediate language, System F. Simon spends a nice chunk of time in this conversation explaining this. It's a rather excellent approach. We only touch on C--, but I have a feeling I'll be interviewing Simon again in the future. How has the language evolved over the years? What's Simon working on these days (besides evolving Haskell, he's helping to make general purpose computing education for the masses much better!)? What's next? What are the big problems he and others are tackling with respect to moving Haskell forward? As always, it's a real pleasure to converse with and learn from Simon. His passion, enthusiasm, and intelligence are infectious (well, maybe not the intelligence part—you're born with the smarts you have. So, I didn't get smarter by talking with Simon, but I sure learned a lot!). Very few people are able to explain complex concepts in ways mere mortals can understand and assimilate. Simon is one of these people. (Here's the video referenced at the beginning of this conversation.) Simon's YOW! speaker page Tune in. Enjoy. Learn. The YOW! Developer Conference offers outstanding opportunities to learn more about the latest practices, technologies, and methodologies for building innovative software solutions as well as the chance to meet and network with international software experts and other talented developers in Australia. Thanks to Dave Thomas and the event's excellent staff - Mary Catherine (MC), Lisa, Aino, Melissa, and others - for inviting me to this excellent pure developer event and thanks to all of the speakers for letting me take some of their time to record conversations for Channel 9. If you live in Australia, or aren't too far away, or just like to travel (who doesn't?), then you need to go to this yearly event. It's outstanding. There are many great developers down u

Why it's here

3 people recommend this

What people say. Recommended for its explanation of data parallelism and concurrency challenges in Haskell.

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On “A new `scheduler` library.”

I think here is a great explanation of the problem by SPJ that this library is good for solving: [video \`scheduler\` will not do any flattening, as in data parallel haskell, but instead it allows the programmer to specify which chunks of your data structure should be processed in separate threads, because the programmer knows which parts of the computation they want to do have no dependencies on each other.
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