COMS W4995 001 Parallel Functional Programming Fall 2023

General Information

Class meets Mondays, Wednesdays 5:40 - 6:55 PM in 633 Mudd.

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 6	Introduction Basic Haskell
Mon Sep 11	(Basics contd.)
Wed Sep 13	Types and Pattern Matching
Mon Sep 18	(Types contd.)
Wed Sep 20	No lecture
Sun Sep 24	(no lecture; turn in homework)		Homework 1 .hs file
Mon Sep 25	(Types contd.)
Wed Sep 27	Recursion and Higher Order Functions
Mon Oct 2	(Recursion contd.)
Wed Oct 4	Using and Defining Modules
Sun Oct 8	(no lecture; turn in homework)		Homework 2 .hs file
Mon Oct 9	I/O
Wed Oct 11	Functors
Mon Oct 16	(Functors contd.)
Wed Oct 18	Monads
Sun Oct 22	(no lecture; turn in homework)		Homework 3 .hs file
Mon Oct 23	(Monads contd.)
Wed Oct 25	Lazy and Parallel Evaluation
Mon Oct 30	Strategies
Wed Nov 1	(Strategies contd.)
Sun Nov 5	(no lecture; turn in homework)		Homework 4 .zip file
Mon Nov 6	Election Day Holiday
Wed Nov 8	Profiling
Mon Nov 13	The Par Monad
Wed Nov 15	The Haskell Tool Stack
Mon Nov 20	Repa: Regular Parallel Arrays
Wed Nov 22-24	Thanksgiving Holiday
Mon Nov 27	Accelerate: GPU Arrays		Project Proposal
Wed Nov 29	The Lambda Calculus
Sun Dec 3	(no lecture; turn in homework)		Homework 5 .zip file
Mon Dec 4	(Lambda contd.)
Wed Dec 6
Mon Dec 11
Wed Dec 20	Final Project Report and Presentations

Teams

PFSS: Parallel File System Stats Report Files Matthew Nelson

PPTG: Parallellized Procedure Terrain Generation Report Files Divjot Bedi

MaximalClique: Fast Fourier Transform (GS) Proposal Report Files Xuezhen Wang and Songheng Yin

ParaSet: Set Card Game Player (GS) Proposal Report Files Ellen Guo, Ryan Xu, and Cindy Zhu

PokerEquity: Poker Hand Evaluator (GS) Proposal Report Files James Fay and Lance Wong

PSGD: Parallel Stocastic Gradient Descent (GS) Proposal Report Files Rishabh Ganesh, Yealin Park, and Yue Sun

Simplex: Parallel Simplex Linear Programming Solver (GS) Proposal Report Files Bereket Molla

trafficsim: Parallelized Traffic Simulation (GS) Proposal Report Files Denzel Farmer and Andrew Yang

WFS: Map-Reduce Word Frequency Search (GS) Proposal Report Files Patricia Luc, Arush Sarda, and Sarah Yang

Hitori: Logic Puzzle Game (SE) Proposal Report Files Ava Hajratwala and Peter Yao

Howard: Ray-Casting Simulation (SE) Proposal Report Files Akash Nayar and Justin Peng

MonteParSim: Monte Carlo simulations (SE) Proposal Report Files Sparsh Binjrajka, Anna Christensen, and Griffin Newbold

NW: Needlemam-Wunsch Sequence Alignment (SE) Proposal Report Files Phillip Le Jr. and Emily Lo

TraderContagion: Agent-based Stocastic Model of Markets (SE) Proposal Report Files Tsigemariam Assegid

2048Solver: Puzzle Solver (SR) Proposal Report Files Alexander Bala and Michal Hajlasz

8-Parzzle: 8-Puzzle Solver (SR) Proposal Report Files Ruth Lee, Ahmad Rawwagah, and Kimberly Tsao

AlphaGambit: Minimax Chess Solver (SR) Proposal Report Files Abhishek Chaudhary, David Zhang, and Anthony Zhou

CheckersBot: Checkers Solver (SR) Proposal Report Files Maria Catarina Coelho and Kavika Krishnan

MatrixBFS: Parallel BFS (SR) Proposal Report Files Blake Appleby, Jonathan Hall, and Ryan Wee

MazeSolver: Rat-in-a-Maze solver (SR) Proposal Report Files Samya Ahsan, Nicole Lin, and Alice Wang

UTTSolver: Ultimate Tic-Tac-Toe Solver (SR) Proposal Report Files HASAN ALQASSAB and Fernando Macchiavello Cauvi

Life: Conway's Game of Life (WQ) Proposal Report Files Mark Mazel

NNS: Nearest Neighbor Search (WQ) Proposal Report Files Kevin Jiang, Jeannie Ren, and Joshua Zhou

StarFinder: Constellation Identifier (WQ) Proposal Report Files Yumeng Bai, Stella Park, and Michelle Tang

NaiveBayes: Naive Bayes Classifier (WQ) Proposal Report Files Amy Qi and Jiakai Xu

TSP: Genetic Algorithm Traveling Salesman Problem (WQ) Proposal Report Files Maximo Jalife and Fernando Camurugy Notari

VRP: Vehicle Routing Problem using ACO (WQ) Proposal Report Files Vincent Geiger and Siyi Hong

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 in groups of 2 or 3. 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.

Links

• PFP from Fall 2022

• PFP from Fall 2021

• PFP from Fall 2020

• PFP from Fall 2019