wiki:Other/Summer/2023/Inference

Version 4 (modified by LakshyaG42, 17 months ago) ( diff )

Resilient Edge-Cloud Autonomous Learning with Timely inferences

Project Advisor and Mentors: Professor Anand Sarwate, Professor Waheed Bajwa, Nitya Sathyavageeswaran, Vishakha Ramani, Yu Wu, Aliasghar Mohammadsalehi, Muhammad Zulqarnain

Names: Shreya Venugopaal, Haider Abdelrahman, Tanushree Mehta, Lakshya Gour, Yunhyuk Chang

Objective: The purpose of this project is to use ORBIT in order to

Main objectives

  • learn how to design and run experiments on ORBIT
  • prototype a handoff scheme for ML prediction
  • develop a latency profiling framework for MEC-assisted machine learning

– Split the network, early exit, simulate multiple CPU speeds, network delays

Progress

*Week 1 Goals

  • Team introductions
  • Kickoff meetings
  • Refining and understanding research questions
  • go over goals for the summer

For next week:

  • Go through WINLAB orientation (TBD)
  • Reading for next time:
  • PPA Chapters 1 and 2
  • Coding:
  • install python (via Anaconda or something else)
  • go through the interactive intro to python online or by downloading the notebook
  • Review the basics of Python linked from the UT Austin site to learn basic syntax, flow control, etc.

*Week 2: Goals: Summary:

  • Basics of pattern recognition and Machine Learning (PPA - Patterns, Predictions, Actions)
  • set up an instance using pytorch on an Orbit node
  • Created a node image with Pytorch
  • Basics of Pytorch
  • Created small Machine Learning models
  • Loaded the Modified National Institute of Standards and Technology (MNIST) database onto the node

computed the second moment matrix

  • Did PCA and SVM on MNIST

Next Steps:

  • Create and train a “small” and “large” Neural Network
  • Attempt to simulate the difference between their performances at inference

Links: Week 3: Goals: Summary:

  • Created and Trained a ‘Small’ and ’Large’ Neural Networks
  • Compared their performances on the CIFAR10 dataset
  • Established connection between two nodes
  • Communicated test data between nodes to compare accuracy and delay between our NN models
  • Need to serialize by bytes instead of transferring as strings
  • Had a discussion on various research papers related to our project

Next Steps:

  • Send the data as bytes instead of strings
  • Calculate the times for transfer & processing
  • Read more papers related to stuff about early exit and edge cloud computing
  • Divide data into “chunks” for faster and more efficient transmission
  • Design experiments to test different architectures and implementations of Early Exiting and Split Computing
  • Track and add Age of Information Metrics

Presentation links:

  • Link - Lakshya
  • Link - Shreya
  • Link - Haider
  • Link - James
  • Link - Tanushree

Week 4: Goals Summary Next Steps

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