NumNum A matrix manipulation language Meet our team Art Zuks: - - PowerPoint PPT Presentation

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Feb 01, 2024 223 likes •445 views

NumNum A matrix manipulation language Meet our team Art Zuks: Kaustubh Gopal Paul Czopowik: k: Sharon Chen: David d Tofu: System Chiplunka kar: r: Manager Tester Tester Architect Language GS SEAS '19 SEAS '19

SLIDE 1

NumNum

A matrix manipulation language

SLIDE 2

Meet our team

Art Zuks:

System

Architect

CSMS

Kaustubh Gopal Chiplunka kar: r:

Language

Guru

MSCE

Paul Czopowik: k:

Manager
GS
CS Major

Sharon Chen:

Tester
SEAS '19
CS major

David d Tofu:

Tester
SEAS '19

SLIDE 3

Project Planning

We used many cutting-edge tools to help manage our project workflow

SLIDE 4

Development Timeline

Floats C style le function

declaration n in favor vor of Pyth ython

n Func

Pri rint nt function

Hello lo World ld! Strings rings Working king AST with h Matrixe rixes Matrix rix take kes any type Matrix rix access Static Arrays ys LLVM elif, bytes es, impli licit type e conver ersio sion file le I/O Demo

SLIDE 5

Test Suite

SLIDE 6

About the Test Suite

While we coded
For corner cases
For semantic checking,

codegen, pretty-printing

For both our syntax and

language logic

Wrote fails
Built upon the Micro-C test

suite

How We Wrote It

SLIDE 7

An Example

Element-Wise Multiplication Semantic Checking Tester

SLIDE 8

numnum

A simple le C-like ike matrix trix manipulation pulation languag age

Stack allocated arrays support Matrix
File I/O
Implicit casting

SLIDE 9

Quick guide for Programming in numnum

SLIDE 10

File IO

Reads into byte, int and float matrix from a binary file
Writes out matrices to files
Properly closes file descriptors for the user

SLIDE 11

Read

SLIDE 12

Write

SLIDE 13

Type Casting

Completely implicit
Converts to the type that is being assigned to
For binary operations converts right side to left side type

SLIDE 14

Operation Casting

SLIDE 15

Assign Casting

SLIDE 16

Demo 1

Image Manipulation

SLIDE 17

Colored to BW image conversion
Blurring with a Gaussian Blur filter
Edge detection using kernels

Image Transformation

SLIDE 18

Using a python script we strip off the headers of the image
Read the image into an array
Read the RGB values into float temp variables, using implicit type

conversion

Perform a weighted sum of rgb values
Assign the float sum back to all the rgb values
Write back to the same image

Image Transformation

SLIDE 19

Reflection

Mirror

Flip

SLIDE 20

Demo 2

Optical Character Recognition (OCR) with MNIST

SLIDE 21

Used the MNIST database to train a simple neural network for handwritten

image recognition

Used File IO to load the trained weights in the program
Again used File IO to load the image RGB values (in bytes)
Performed Accumulation and multiplication of the floats
Go through all the confidence values, search for the biggest one, display the

result

Neural Network Character Recognition