Project 1 (due Feb 21)
Analysis: UMass Scheduling Data
The objective of this project is to analyze the real-world scheduling data.
An example exploration or analysis would be to: simulate this data through each of the schedulers you created in labs 2 and 3 and decide for (e.g., average turnaround time) which scheduler is the best on this real-world data.
Try to write 1-1.5 paragraphs about what you tried and how it turned out. If you have experience and what you explore makes sense as a plot, graphs are always appreciated (but not mandatory – this isn’t a viz class).
Writing: Q1: How do we run multiple programs at the same time?
Try to write 1-2 paragraphs on this question as we’ve discussed in class, read in the book, worked on in labs.
What do I turn in?
- A zip file (if you have multiple python files to share with me) or just a .py file if you only have one.
- A PDF file (strongly preferred over docx) containing your written analysis and writing (Q1).
Any more advice?
I’m still around on our slack channel!
It’s OK to through out some data.
If you care about turnaround time, you could throw away all cancelled / errored jobs, and the jobs that never finished. Those jobs may be useful to you if you care about response time….
Hint: Parsing DateTime information
start_time = datetime.strptime(row, "%Y-%m-%dT%H:%M:%S") # As number of seconds since 1 Jan 2020. print(start_time.timestamp())
This project builds on labs:
- Lab 2: Oracle Schedulers (due Feb 11)
- Lab 3: MLFQ xor Lottery Ticket Schedulers (due Feb 18)