Affordable Large RAM Subsystem July 2021
Big Memory - A New Computing Paradigm
"Ideally one would desire an indefinitely large memory capacity...It does not seem possible physically to achieve such a capacity. We are therefore forced to recognize the possiblity of constructing a hierarchy of memories." - John von Neumann
In recent years, data is growing at a larger and faster rate. While volatile memory is fast, it is also expensive and limited in storage. Traditional storage model cannot keep up with that growth as large data must be placed in the disk and retrieved when needed. A Big Memory Server is one with RAM subsystem ranging from 6-24 TB, larger than that available on contemporary systems. They enable many data-intensive applications to run in-memory, such as low-latency trading, ML inference, large exhaustion-by-proof enumeration etc... Modern approach such as Intel Optane is closing the gap in the memory hierarchy and solutions exist that are implemented on enterprise level. In our work, we propose an alternative solution using NAND-flash SSD. Our goal is to create HPC system for analytics of scale that would otherwise not be affordable for small datacenters. See our presentation in the upcoming IEEE HPEC conference in September.
GPU-accelerated Supercomputer June 2021
Our private 10 CPU + 4 GPU nodes computing cluster
A project by the BUHPC club, a 10-node Raspberry Pi + 4-node Nvidia Jetson Nano Cluster, networked over Ethernet with master node login. Access granted to club members upon request, we use it to experiment new ideas and distributed programs. Supports OpenMPI 3.0, AMD AOCL, CUDA 11, GCC
A picture I took while setting up the hardwares
Competitive Programming Library May 2021
My setup and custom algorithm for competetive programming.
The repo includes various tricks and techniques I've collected over the years from difference sources as well as my own modifcation. It also has my vim configuration. I will continue to update the library, currently there are several unpushed pieces of algorithms and they need to be tested first. This also serves as a reference for team practices as well as for my students. They are intended to be straight out of the box for easy copy and pasting during contest.
INTLSnip September 2020
A snipping tool that resizes the image intelligently using content aware scaling
I got the inspirtation while getting training data. I wanted a way to avoid squishing image and still preserve the features. The tool is implemented using the algorithm described in this paper
XRAY July 2020
Analyzing CT scans of poential covid patients
I've always been quite curious about the application of deep learning in the medical field. This is my attempt at building a classifier for identifying medical images of Covid patients
I do not claim any diagonstic performance of the model. I was able to get 100% accuracy on the testing data. However this was likely due to a small dataset. This is merely a proof of concept inspired by this paper
EasySchedule December 2019
A planner for scheduling my classes because of the tedious gen ed credits
The GUI is built in JavaFX, feel free to make any modification as needed. The data is written into CSV for parsing, you will probably need to add more to it yourself if you're not majoring in CS. Just fill the parameters. Funny enough, right after I built the planner my friend told me they introduced a system that calculates it for you.