COMS W4995 003 Parallel Functional Programming Fall 2019

General Information

Class meets Mondays, Wednesdays 5:40 - 6:55 PM in 417 Mathematics.

Staff

Overview

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.

Schedule

Date	Lecture	Notes	Due
Wed Sep 4	Introduction Basic Haskell
Mon Sep 9	Types and Typeclasses
Wed Sep 11	Basic Function Definitions
Mon Sep 16
Wed Sep 18	Recursion and Higher Order Functions
Mon Sep 23
Wed Sep 25	Using and Defining Modules		Homework 1 .hs file
Mon Sep 30
Wed Oct 2	User-Defined Types
Mon Oct 7
Wed Oct 9	I/O
Fri Oct 11	(no lecture; turn in homework)		Homework 2 .hs file
Mon Oct 14	(No lecture)
Wed Oct 16	(No lecture)
Mon Oct 21
Wed Oct 23	Functors
Fri Oct 25	(no lecture; turn in homework)		Homework 3 .zip file
Mon Oct 28
Wed Oct 30	Monads
Mon Nov 4	Election Day Holiday
Wed Nov 6
Mon Nov 11
Wed Nov 13
Mon Nov 18
Wed Nov 20	Lazy and Parallel Evaluation
Fri Nov 22	(no lecture; turn in homework)		Homework 4 .zip file Project Proposal
Mon Nov 25
Wed Nov 27	Thanksgiving Holiday
Mon Dec 2	Strategies
Wed Dec 4
Mon Dec 9	The Par Monad
Wed Dec 18	(no lecture)		Project report and code

Teams

random-graphs: Proposal Report Files Dhruv Singh

2048-puzzle1: (AL) Proposal Report Files Tri Do

freecel: (AL) Proposal Report Files Joe Huang

crossword: (AL) Proposal Report Files Rose Huang and Biqing Qiu

3-partition: (AL) Proposal Report Files Hyeon-U Kang

suicide-chess: (AL) Proposal Report Files Alexander Khoma and Jakwanul Safin

othello: (AL) Proposal Report Files Kaiji Lu

2048-puzzle2: (AL) Proposal Report Files Colin Brown and Jonathan Rich

boggle: (AL) Proposal Report Files Khyber Sen

othello-2: (AL) Proposal Report Files Chengtian Xu

gomoku: (AL) Proposal Report Files Zheng Yao and Qinhan Zhou

cellular-fluid: (JH) Proposal Report Files Rongcui Dong

HipgRap: (JH) Proposal Report Files Bicheng Gao and Kangwei Ling

ray-tracer: (JH) Proposal Report Files Garrison Grogan

n-body: (JH) Proposal Report Files Kundan Guha

ray-tracer2: (JH) Proposal Report Files Jiakang Guo

polygon-rendering: (JH) Proposal Report Files Joshua Learn

particles: (JH) Proposal Report Files Morgan Navarro

sph: (JH) Proposal Report Files Zachary Schuermann

r-tree: (JH) Proposal Report Files Samurdha Jayasinghe Mudi and Ge Wang

mandelbrot: (JH) Proposal Report Files Amanda Liu

D*-Lite: (PT) Proposal Report Files Eric Chase

auto-complete: (PT) Proposal Report Files Siwei Chen

n-grams: (PT) Proposal Report Files Dave Epstein

ALife: (PT) Proposal Report Files Alex Gajewski

word-break-ii: (PT) Proposal Report Files Michelle Mao and Hana Mizuta

knapsack: (PT) Proposal Report Files Shaohua Tang and Jing Wang

knapsack-2: (PT) Proposal Report Files Jt Timpanaro

robbie: (PT) Proposal Report Files Eli Whitehouse

collaborative-filtering: (PT) Proposal Report Files ZHOU ZHUANG

auto-suggest: (PT) Proposal Report Files Tomer Zwi

graph-coloring: (SE) Proposal Report Files Ishan Guru and Haneen Mohammed

sodoku: (SE) Proposal Report Files Jiaheng He

map-reduce1: (SE) Proposal Report Files Yimin Hu

mutual-friends: (SE) Proposal Report Files Yefri Gaitan and Ecenaz Ozmen

kenken: (SE) Proposal Report Files Harry Smith

map-reduce2: (SE) Proposal Report Files Jian Song and Ziao Wang

map-reduce3: (SE) Proposal Report Files Sambhav Anand and Kanishk Vashisht

topo-sort: (SE) Proposal Report Files Raymond Li and Wendy Wang

pagerank: (SE) Proposal Report Files Zefeng Liu and Xi Yang

My favorites

The Project

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:

1. A one- or two-page proposal that gives the TAs and me an inda of what you plan to do so we can give you feedback about restricting or increasing the scope. Upload a PDF file to Courseworks describing your project and team members, if any.
2. A report describing your project: what you implemented and how, some performance figures indicating how much better your solution runs in parallel (e.g., time its execution on one core and compare that to running it on multiple cores), and a full listing of the code you wrote. Upload a multi-page PDF file to Courseworks; due during Finals Week.
3. Along with your report, submit a .tar.gz file including the code and test cases for your project. Make it so I can compile and run it, perhaps by including a README file with instructions for running it with the Haskell Stack. Due with the repot.

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

Resources

• Miran Lipovaca. Learn You a Haskell for Great Good! No Starch Press, 2011.
• Bryan O'Sullivan, Don Stewart, and John Goerzen. Real World Haskell. O'Reilly, 2008.
• Simon Marlow. Parallel and Concurrent Programming in Haskell. O'Reilly, 2013.
• The Parallel Functional Programming course at Chalmers University, Sweden.

Class Policies