Here are the
for today’s DEFUN tutorial: Multicore Programming in Haskell Now!
Multicore computers are here: is your programming language ready for it?
Haskell is: you can take an off-the-shelf copy of GHC and write high performance parallel programs right now. This tutorial will teach you how to exploit parallelism through Haskell on your commodity multicore machine, to make your code faster. We will introduce key parallel programming models, as implemented in Haskell, including:
- semi-explicit parallelism via sparks
- explicit parallelism via threads and shared memory
- software transactional memory
- data parallelism
and look at how to build faster programs using these abstractions. We will also look at the engineering considerations when writing parallel programs, and the tools Haskell provides for debugging and reasoning about parallel programs.
This half-day tutorial will teach intermediate functional programmers with no previous parallel programming experience how to write, reason about and run parallel Haskell programs, using a range of parallel programming models. Each model will be introduced with motivating examples, and exercises to develop familarity with the model in question. By the end you should have an understanding of which parallelism abstraction to use in which circumstance, and be able to go to work writing multicore capable programs in Haskell.
I’m busy preparing a tutorial for DEFUN on Saturday, and was putting together the “further reading” slides for the attendees, so they have material to go to for deeper reading.
Here’s my basic “How to learn about parallel programming in Haskell” reading list.
Learn Parallel Haskell
- “Real World Haskell”, O’Sullivan, Goerzon, Stewart. O’Reilly 2008. Ch. 24, 25, 28.
- Step by step guide to implicit and explicit parallelism in Haskell, and transactional memory
- “A Tutorial on Parallel and Concurrent Programming in Haskell”, Peyton Jones and Singh. 2008
- General overview of explicit and impliict parallelism in Haskell, as well as transactional memory and data parallel Haskell
- “Runtime Support for Multicore Haskell”, Marlow, Peyton Jones, Singh. 2009.
- Describes the architecture of the sparks and parallel GC
- “Parallel Performance Tuning for Haskell”, Jones, Marlow, Singh, 2009
- Introduces ThreadScope, and methodical parallel performance advice
- “Harnessing the Multicores: Nested Data Parallelism in Haskell”, Peyton Jones, Leshchinkskiy, Keller, Chakravarty, 2008.
- the Barnes-Hut algorithm in Data Parallel Haskell
- “Haskell on a Shared-Memory Multiprocessor”, Harris, Marlow, Peyton Jones, 2005
- The original SMP runtime implementation paper
- “Beautiful Concurrency”, Peyton Jones, O’Reilly 2007
- Introduction to software transactional memory
- “Composable memory transactions“, Harris, Marlow, Peyton Jones, and Herlihy, 2005
- Introduces composable software transactional memory
- “Algorithm + Strategy = Parallelism”, Trinder, Hammond, Loidl, Peyton Jones, 1998.
- Introduces parallel sparks and strategies
- “Concurrent Haskell”, Peyton Jones, Gordon, Finne, 1996.
- Introduces concurrent Haskell and forkIO.
- “Tackling the Awkward Squad”, Peyton Jones, 2001.
- Classic introduction to concurrency in Haskell (and IO), and how to use MVars and Channels.
Does anyone else have favourite learning materials for parallel and concurrent programming in GHC Haskell?