Autumn
2-days
Dates
On-boarding Tue Dec 3, 1-2pm
Thur-Fri Dec 5-6, 9-16
Content
2nd day: Pandas more parallel/big data
Meeting 11 Dec 14.15
Agenda:
we have to draw up plans for NAISS training in 2025
please work on your plans for 2025.
dates should be given.
Joachim was instructed that plans for early in 2025 should be pretty precise. If the planing for the end of 2025 is more vague this would be understandable.
Meeting 27 Nov at 14
Status
Registrations 59
OS Windows: 26 Linux: 17 macOS: 16Python knowledge: None: 7 Basic/beginner: 15 Intermediate: 27 Proficient/expert: 10
Projects
storage on its way for LUNARC
Continuous Integration
spelling in order
links needs revisit
manually fix for missing
-matlabin 4-day course links
rst linter
not activated yet
Working code on all centres
Björn/Jayant has not tested yet
Birgitte half-ways
don’t forget Tetralith
Prerequisites
2 files
“Preview” cheat-sheet
lessons
syllabus/index 20
keep log in and exercise fix here
load+run+scripts+import 30
works everywhere
packages/venvs (reducing time) 50–> 30
just needed thinks
exercise including making the env
please help to define packages needed on different systems (issue)
compute nodes
show how to load jupyter, VScode (Pedro from local), spyder (Rebecca)
on-demand (10-15 min)
split
batch 30
interactive (seq) 20
IDE 15
users starts interactive for the afternoon 5h
matplotlib/analysis
spyder
pandas
add for summary cheat-sheet
Discuss schedule
Too much material?
Change timings?
ToDos
Content
Test code
all centres
tabs for
lunarc
nsc
Meeting Nov 20
Status
Registrations
40
~5 at lunarc
8-10 at UPPMAX
~5 Umeå/Luleå
~20 at NSC
Projects
4 places
nsc for new users
Content
added NSC to many parts
jupyter
we are responsible for our own sessions that is works everywhere
IDES presented before lunch
Rebecca focuses on using the tools
jupyter format–> md/rst
VSCode is on tetralith
just show how to load
let them choose if used later in course
GPU no much changes needed!
packages.rst may be updated for tetralith etc
more packages need to be installed by user
analysis day 2
conversion needed (perhaps link from Birgitte)
numba moved to parallelism
parallelism
identify needed packages
Big data: start work
DL: started
Discuss
requirements for venvs
different for different clusters
YES
JUST Tetralith py/3.10.4 for all sessions
yes
Exercise time: At least 25 % Votet YES
ToDos
storage at Cosmos RP
mermaid for NSC BC
all define required packages for the python version we will use
BC will collect
let user define problem in text before course starts
schedule fixed by wednesday
timings
no moving afterwards
next meeting: 14.00 Wednesday 27
Meeting 13 Nov
Status
Registrations
ML
cleaned!
to start from
horovod in extra?
Discuss
ML
do not show Theano (old)
keras together with TF (dependency)
needs updates (focus on 3.11.5/8 at UU)
pytorch and TF on Lunarc/HPC2N
sklearn at HPC2N
seaborn on LUNARC
VSCode
test the limits and possibilities
JuliaCall works in another way at tetralith
Next meeting
Wednesday Nov. 20 at 14:00
Meeting 8 Nov
Agenda
Status
Possible updates/plans
Status
UPPMAX maintenance day before (Wed)
Involve Tetralith/Dardel? (must evidently do (this)
waiting for input from UPPMAX sysexps
course project/staff
apply for tetralith! (GPU is available for us, it seems)
DONE!
dardel wait to include this time
Registration
32 registered
Issues
prereqs: BC & RP rather well in advance
next week…
ML:
BB starts to look the status of the present stuff (by Tue)
then meet with Jayant
Materials
Python >=3.11.5
Day 1 morning
Day 1 afternoon
Birgitte takes the GPU (Pedro away)
Day 2 morning
Day 2 afternoon
Possible updates/plans
BC: Spyder can be installed in venv
need to check more details
EB only up to foss2020
anaconda is providers first choice but not my favorite!
on cosmos: on demand, type depencency in “additional text box”
RP check vscode how it is run? -Currently only on FE
Jayant runs vscode
ToDos
look up bioconda
MIT license(?) it seems
Meeting Oct 31
Agenda
Status
Evaluation of last sessions
Schedules and teachers
Possible updates/plans
Status
Registrations are ongoing
21
bio/atmos/astro/etc
Advertisement
The goal for the course is that you will be able to
Load Python modules and site-installed Python packages
Create a virtual environment and install your own Python packages to it
Write a batch script for running Python
Use Python in parallel
Use Python for ML
Use GPUs with Python
Use pandas
Learn about matplotlib
Prerequisites: familiarity with the LINUX command line, basic Python
add pandas basics
Evaluations
May course HPC-Python
Load and run
Include in On-boarding?
On Load/run session: Short summary.
No recording at THAT time, interaction for those with problems
NOTES:
On-boarding
PRESENT LOGIN AND MODULE LOADING
No login session 5-6 Dec?
or 9.00-10.00: login/load/editor/run/tar balls
Install package at 10
Fine!?
Batch mode:
Perfect!
Interactive on compute node (be clear en session title)
Let students try Jupyter in exercise
more hands-on
NOTE: Look into Spyder
Parallel computing
More hands-on
GPUs
Same material but faster?
Or Extra material?
exercises
ML
More exercises?
NOTE: will extend!
More links to deeper material!!
OBS! Above is just the old material
Summary of earlier discussions
1st day: almost like before, shorten basics things
2nd day: Pandas more parallel/big data
Discuss the division of the days
First day things not requiring batch and ML and GPU
ask compute node for interactive work
basic slurm
also GPU
Jupyter/spyder
pandas/matplotlib/seaborn?
Second day: ML and parallelisms
Vote YES
Vote NO: BB
it is in the info already
Preliminary schedule
Instead
First day
9.00 Login/load/run/tarball [name=Birgitte] + all
10.15 packages/virt envs (short) [name=Björn]
11.15 basic slurm [name=Birgitte]
interactive
get gpus
start jupyter/spyder
13.00 analysis (75min) [name=Rebecca]
using IDE work environment
jupyter/spyder(?)/VScode(?)
matplotlib 60
14.30 GPU 60 [name=Pedro?]
15.30 Use cases + Q/A [name=All]
16.35 Ending with evaluation
Second day 9-17
9.00 Analysis 105m [name=Rebecca]
pandas 75
seaborn 30
11.00 Parallelism 60-75 60+15m after lunch [name=Pedro]
MPI
dask
processes
13.15 Big data 45 [name=Björn]
csv?
xarray?
netcdf
hdf5
chunking (dask+pandas?)
14.15 ML+DL 2x45 min [name=Jayant]
pytorch
tensorflow
sklearn
16.00 Use cases + Q/A [name=All]
16.45 Ending with evaluation
Evaluation in May?? (already discussed above)
big data
point to other on-line material for specific science topics
To discuss further
jupyter
extend parallelism and ML
in application: ask knowledge of parallel, slurm, gpu, ML
more course links: https://enccs.github.io/gpu-programming/
rewrite course goal:
Deploy hpc-resources for different problems
not learning the solutions of the problems!
Evaluation of Python day in Oct
Lecturer
Day 1
Session |
Björn |
Birgitte |
Pedro |
Rebecca |
|---|---|---|---|---|
“Syllabus”+intro |
X |
|||
Load-run+packages |
X |
|||
self-inst. isolated |
X |
|||
batch |
X |
|||
parallel |
X |
|||
interactive |
X |
|||
GPU |
X |
|||
ML (incl exercises) |
X |
|||
Exercises (exercises) |
several different rooms |
x |
x |
|
Question session (breakout) |
X |
X |
X |
|
Summary |
X |
X |
X |
Day2
Session |
Björn |
Birgitte |
Pedro |
|---|
Old schedule FIX
Session |
May 2024 |
Suggestions Dec |
|---|---|---|
9.00 “Syllabus” |
30 |
15 |
9.15 Intro |
10 |
10 |
9.25 Load-run + system inst. packages |
35 |
30 |
9.55 break |
15 |
15 |
10.10 self-install. packages + isolated |
46 |
35 |
10:45 batch + arrays |
35 |
35 |
11.05 break during |
10 |
10 |
11.30 interactive + jupyter (together) |
15 (a little too short) |
25 |
12:00 Lunch |
Session |
Dec23 |
Suggestions 15-May-2024 |
|---|---|---|
13.00 parallel |
55 |
60 |
14:00 break |
10 |
|
14:10 GPU |
30 |
40 |
14.50 BREAK |
||
15.05 ML (incl all exercises) |
23 |
30 |
15:35 Sum+eval |
18 |
20 |
15:55 Q/A + extra exercise |
0 |
35 |
16:00 END-OF-DAY |
||
sum |
150 |
ToDos
look into spyder
installed on UPPMAX?
tunnelling YES
allowed at HPC2N? NO