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application-failure-prediction

This assignment deals with predicting failure of application executions (referred to as “job”) on Purdue ITaP’s central computing cluster. This is data that we have collected, collated, and analyzed as part of a project from the National Science Foundation (NSF) (Computer System Failure Data Repository to Enable Data-Driven Dependability Research,” Proposal No. CNS-1513197).

assignment1

Stencil code for assignment1

curious-rl

Curiosity-driven Exploration by Self-supervised Prediction

d2l-en

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 200 universities.

ece565-2022

A repo to assignment and project descriptions for ECE 565 in 2022

ece637

embeddedvision

An introductory graduate course on "Computer Vision for Embedded Systems"

episodic-curiosity

Tensorflow/Keras code and trained models for Episodic Curiosity Through Reachability

examples

TensorFlow examples

git_basics

git_merge

git_rebase

knowmadninja.com

large-scale-curiosity

Code for the paper "Large-Scale Study of Curiosity-Driven Learning"

lf-building-a-risc-v-cpu-core

map-reduce-word-count-openmp-mpi

map-reduce-word-count-openmp-mpi-1

This repository contains an implementation of counting words in many files using the map-reduce algorithm. The algorithm is implemented in both OpenMP and MPI. A serial implementation is also available for perf evaluation.

mcs-mobility-trace

We conducted a real-world mobile crowdsensing campaign on our university campus (Purdue) over one month (Feb 7 - Mar 7, 2018) with 50 users to evaluate CROWDBIND (our EWSN 20 paper) plus 4 competing solutions. The students went about their daily routine with their smartphones running the five different software packages, collecting sensor data (pressure). This is the anonymized mobility trace of these 50 students over a 100 sq. km. area.

minance

Developing code for money making

noreward-rl

[ICML 2017] TensorFlow code for Curiosity-driven Exploration for Deep Reinforcement Learning

ray

An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.

sitting-posture-recognition

Detects the sitting position of a person

ultimate-fastapi-tutorial

The Ultimate FastAPI Tutorial

work

workflow_testing

Repository to test workflow integration with CI/CD Pipelines