|COMS W4995 003
Parallel Functional Programming
Class meets Mondays, Wednesdays 5:40 - 6:55 PM in Online; see Courseworks.
|Prof. Stephen A. Edwardsemail@example.com||F 2-4||Online|
|Shravan Karthikfirstname.lastname@example.org||Th 2-4||Online|
|Benjamin Flinemail@example.com||W 7-9||Online|
|Garrison Groganfirstname.lastname@example.org||F 5-7||Online|
Prerequisites: COMS 3157 Advanced Programming or the equivalent. Knowledge of at least one programming language and related development tools/environments required. Functional programming experience not required.
Functional programming in Haskell, with an emphasis on parallel programs.
The goal of this class is to introduce you to the functional programming paradigm. You will learn to code in Haskell; this experience will also prepare you to code in other functional languages. The first half the the class will cover basic (single-threaded) functional programming; the second half will cover how to code parallel programs in a functional setting.
|Wed Sep 9||Introduction
|Mon Sep 14||Types and Typeclasses
|Wed Sep 16||Basic Function Definitions
|Fri Sep 18||(no lecture; turn in homework)
||Homework 1 .hs file|
|Mon Sep 21||Recursion and Higher Order Functions
|Wed Sep 23||(Recursion contd.)
|Mon Sep 28||Using and Defining Modules
|Wed Sep 30|
|Fri Oct 2||(no lecture; turn in homework)
||Homework 2 .hs file|
|Mon Oct 5||User-Defined Types
|Wed Oct 7|
|Mon Oct 12||I/O
|Wed Oct 14|
|Mon Oct 19||Functors
|Wed Oct 21||Monads
|Mon Oct 26|
|Wed Oct 28|
|Mon Nov 2||Election Day Holiday|
|Wed Nov 4|
|Mon Nov 9|
|Wed Nov 11|
|Mon Nov 16||Lazy and Parallel Evaluation
|Wed Nov 18|
|Mon Nov 23|
|Wed Nov 25||Thanksgiving Holiday|
|Mon Nov 30|
|Wed Dec 2|
|Mon Dec 7||The Par Monad
|Wed Dec 9|
|Mon Dec 14|
The project should be a parallel implementation of some algorithm/technique in Haskell. Marlow parallelizes a Sudoku solver and a K-means clustering algorithm in his book; these are baseline projects. I am looking for something more sophisticated than these, but not dramatically more complicated.
Do the project alone or in pairs. List all your names and UNIs in the proposal and final report
There are three deliverables:
Strive for a little well-written, well-tested program that handles everything gracefully rather than a large, feature-filled system. If you're short on time, drop a feature in preference to improving the code you have.
Other project ideas include any sort of map/reduce application, graphics rendering, physical simulation (e.g., particles), parallel grep or word count, a Boolean satisfiability solver, or your favorite NP-complete problem. If your program is algorithmically simple (e.g., word count or word frequency count), it need to scale to huge inputs. AI (as opposed to machine learning) applications, such as game playing algorithms, are generally a good idea. Algorithms that have a lot of matrix multiplication at their core (e.g., deep learning) are less suitable.
Feel free to ask the instructor or TAs for project advice or criticism