home@jellyware:~$
Hi, I'm Jay!
home@jellyware:~$
about_me
projects
This site
- Built using Next.js, React.js, Typescript & SCSS
- Deployed to Vercel and domain is protected by Cloudflare
- CV is an API endpoint that serves my CV
- Terminal animation at the top is built from scratch with React and SCSS
Jellis
- Implementation of C++ in Redis
- Supports multiple clients simultaneously - implemented using the boost ASIO library with a event loop and TCP sockets
- Developed a parser and encoder for the Redis serialization protocol (RESP)
- Currently only supports the in memory database but I’m working on data persistence with RDB.
Neural Network from scratch - using Python and NumPy
- Implemented backpropagation to find the gradient of the loss with respect to each neuron
- Implemented gradient descent to update the weight and reduce the loss
C90 to RISC V assembly - C++
- Achieved 89% - passing 179 out of 201 tests
- Added support for: chars, ints, floats (IEEE 754), arrays, pointers, for, while & do while loops, if statements, switch statements, functions, strings, typedef keyword, arithmetic (pre-increment operator, post-increment, etc.), constants, local & global variables (including correct scoping), enums, sizeof
RISC V 32I Pipelined CPU - System Verilog & C++
- Designed and implemented the hardware for pipelining the CPU
- Designed and implemented a hazard unit that could stall, flush instructions, and pass data to previous stages to prevent stalls
- Wrote test benches in C++ to run programs on the CPU
mini grid project
- Create a full-stack app with Next.js, Typescript, Tailwind CSS and Python
- Displayed real-time data from Raspberry Pi Picos using MQTT
- Programmed the Raspberry Pi Picos to communicate via MQTT
- Used MongoDB to store previous data and plot it using Recharts.js
- Deployed the MQTT broker to an AWS EC2 instance and shared the web app using ngrok
- Built a neural network using PyTorch to predict the buy price of electricity