ASPP/2024-heraklion-parallel-python
8
0
Fork 1
Code Issues Pull requests Projects Releases Packages Wiki Activity Actions

updated readmes for exercises

Browse source
This commit is contained in:
Jenni Rinker 2024-08-29 19:00:45 +03:00
parent 86e99bb814
commit af567b80b0
3 changed files with 41 additions and 2 deletions
Download patch file Download diff file Expand all files Collapse all files

38
exercises/exerciseC/README.md Normal file
View file

@ -0,0 +1,38 @@
# Exercise C: blending processes and threads
Objective: investigate how the number of processes and threads impacts the
speed-up time of a computation.
## First
For each of the 19 images in the folder `images/`, the `process_images.py`:
(1) decomposes the image using a singular-value decomposition (SVD), (2) removes the
largest singular value and (3) returns the reconstructed image. The script also measures
the time for the computation and saves the result in `timings/`.
You can change the number of processes and threads on a set of images by calling the function
as follows:
```python process_images.py 3 2 images/*```
The code above will use 3 processes and 2 threads to analyse everything in the folder `images/`.
**TASKS**:
0. Familiarize yourself with the code in `process_images.py`. Where is the number of
threads set in the code? Why is it set there? Where is the number of processes set
in the code?
1. Hypothesize what would be a good number of processes and threads for this exercise.
2. Try a couple combinations of processes and threads, look at the saved timings, and see if
the results match your expectations.
## Second
This folder also includes a bash script called `run_with_all_configurations.sh`.
**TASKS**:
0. Open the bash script. What does it do?
1. Execute the bash script in the terminal:
`bash run_with_all_configurations.sh`
Observe what's printed to screen. Does it match your expectations?
2. Open `plot.py` and see what it does. Run the script and view the results. Do they
match your expectations?
3. Add the image as a comment to the Pull Request you opened in Exercise A (or make a
new Pull Request if you need one).

2
exercises/exerciseC/process_images.py
View file

@ -45,7 +45,7 @@ if __name__ == '__main__':
# we need to set the variable before numpy is imported!
os.environ['OMP_NUM_THREADS'] = str(n_threads)
# We delay the import of numpy because we want to set OMP_NUM_THREADS.
# We delay the import of numpy because we have to set OMP_NUM_THREADS before import.
# We delay the import of PIL in case it uses numpy internally.
import numpy as np
from PIL import Image