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# System prepended metadata

title: What people wish to learn in the

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# What people wish to learn in the

* intro
* I need supercomputer powers for my research work, thereby I need some basics connected with using Triton cluster.
* -
* Learn to use Triton
* I want to be able to utilize Triton to boost the learning time of my machine learning model, which currently takes 2 hours to run 1 epoch.
* Triton computing
* I am at beginning stage, so anything related to using Triton are great.
* I have to use Triton for my research project, I'd like to learn how to.
* I am interested to learn how to use triton as well as the other Linux shell servers for running Matlab, Python and Comsol. More hands-on work - less theory.
* "I wish to learn some very useful commands in the level of job submission in triton.
* Also, the types and sizes of the jobs and how to write the job scripts."
* I am interesting in broadening my perspectives about computational research. In the past, I have done small qualitative studies, but - with new open data sources emerging - I would be interested in learning more about the basics of computational research.
* I wish to learn more about the triton environment and how to use it.
* x
* An intro to Triton with R and Python
* I want to be able to utilize Triton to train my machine learning model which requires a cluster of GPUs to train.
* How to use High Performance Computing in simulation
* Basics and good practices on parallelization and on the Aalto HPC cluster.
* Basics of high-performance computing
* Getting insights on how Aalto set up HPC and how I can make the most out of the available computational resources
* I need a power of a supercomputer to conduct my research, however I am kind of a dummy in the topic of scientific computing. Hope this course will help to figure out some basics!
* -
* How to use Triton
* Mainly how to use efficiently the HPC
* Usage of Triton and other Finnish HPC clusters for numerical simulations of finite volume solver coupled with monte carlo codes
* The basic concept of HPC and how to use triton to run COMSOL simulation.
* I would like to learn good practices of data handling, scheduling runs and possibly how to effectively parallelize the tasks effectively to run in the Triton.
* Running programs in triton.
* "I would like to recap the basic SLURM commands, learn about the Triton cluster work process, user accounts, data handling, etc., and also grab a few hints about high-performance computing in general.
* I am mostly using (or planning to use) Triton for COMSOL calculations."
* How to manage our projects efficiently?
* I wish to cover the gaps in my knowledge considering the Triton. I got my introduction from an excelent batchelor student, but I want to be sure there are no major gaps in my knowledge
* I'd be interested to know some of the more advanced features. I've worked out things like array job, environment variables, batch canceing/scheduling jobs etc
* "I have attended HPC about 10y ago and have had a break from using it in between; I hope to hear what has changed meanwhile.
* 
* Priority aim: how to use Triton without bothering other users, e.g. accidentally submitting too large jobs."
* Using Triton
* How to use Triton for my research project.
* learn how to use triton in general
* An introduction to Triton. Greatly appreciated would be if there were a few hands-on scripts/examples/jobs/... that the participants can submit to Triton in order to see the difference between running them locally and running them on the cluster. Maybe also some job management? I did use slurm at some point but found it quite confusing at the time. All in all I can operate on a Linux machine but am by no means an expert user. So that's roughly the level of difficulty I would be hoping for :).
* Understand the potential of HPC and how to program and run pipelines in Triton.
* Some practicalities of computing even if I am not doing a scientific project
* How to use distributed computing source that is available in Aalto.
* nothing specific. just eager to learn something new that might improve my work.
* I'm a regular user of python/anaconda environment for modelling/analysis, but expect I can pick up new practices/tips. Also interested in the intro to the Triton cluster and HPC
* I would like to improve my knowledge about scientific computing.
* basics of scientific computing
* I want to start using the Triton cluster for simulation.
* I know nothing about high performance computing and would like to learn about the basics.
* Speed up my computation.
* What is the difference of OpenMP and OpenMPI and other interfaces. Parallelization across nodes, using job arrays with slurm.
* I just want to get a bit more familiar with the Triton environment and make sure I am following the recommended practices
* Data collection process in live measurements, data storage and management.
* improve training speed of Deep Networks in AI.
* My knowledge on HPC is almost null. Therefore, I'm mostly interested to know the basic of HPC and perhaps recognize how it can be useful to my work.
* I like to improve my computing skills and the performance of my data analysis code/tools.
* some basics about scientific computing.
* I have been using Triton to train machine learning models recently. I have encountered some quotas issues as well as running on multiple GPUs. Thus, I hope to know how to optimize my training process to make better use of triton.
* I would like to improve my computing skill and wish to learn more about the computing tools, code or software for scientific research.
* I have read about HPC but have not practiced it concretely. Would be nice to learn to script properly these types of computational tasks in Bash and a larger environment
* programming languages
* introduction to the Triton cluster, remotely accessing data from elsewhere, parallel processing and job scheduling
* To learn the basics of scientific computing and to get an introduction to HPC with the Triton cluster
* More about using Triton and the possibilities of it. I would be interested in the possibility of running Triton processes from Airflow, Prefect, or some other data workflow management tool.
* How to run many jobs at the same time.
* How to efficiently connect and use HPC machines.
* How to utilize Aalto computing services, how to define requirements for the process you need.
* How to use cluster and what are the different ways to speed up my program.
* Basics about triton.
* I would like to know about the basics of scientific computing.
* Learn how to speedup high performance computing codes
* Scripting, and other basic when using HPC
* We have been doing microbiome analysis from various sources and now we are venturing into machine learning and models building using microbiome data. This course will help us to use the cluster and get familiarised with using CSC and batch jobs submissions.
* I would like t learn about
* New stuff
* to understand computing better
* I wish to get a good hands-on introduction in order to make better use of csc services in my research.
* I will use triton in the computations for my masters thesis. I hope to learn how to improve the performance of my code.
* improve my computing skills and data analysis code/tools using HPC
* High Performance Computing (HPC)
* -
* More interested in HPC kickstart part 2.
* I am interested in learning how to improve my computing skills and the performance of my data analysis code/tools using High Performance Computing and CSC service especially from data fitting and regression perspective.
* I would like to learn the usage of narvi cluster, cuda module etc.
* How to optimize my programming for better speed
* Computational chemistry
* Dana storage management, GPU computing, and parallel computing
* What computational resources I have available to myself in research at Aalto University.
* I'm interested in learning how to use HPC to speed up Monte Carlo simulations.
* Computing with CSC clusters
* How to debug python scripts run on HPC. I loose quite some time with scheduled scripts that eventually crash. What are best practices there?
* I am interested in improving my computing and data analysis skills. Moreover, I want to learn more about HPC and use it in my project.
* Introduction to HPC
* I’d just like to get an overview….
* Getting ideas how to start in the area of scientific computing.
* Scientific computing.
* To learn more about how to run scientific calculations efficiently on HPCs.
* I would like to improve my GPU computing. And, wish to utilize cluster in my simulations.
* I want to learn the new developments happening in computational materials sciences
* I would like to know how to use the HPC cluster to run some challenging tests, either in MatLab or python code
* I'd like to improve my proficiency in the academic HPC environment by reviewing the basics of tools I commonly interact with (coreutils, SLURM) and seeing the application of said tools and best practices from more experienced users and admins
* Improving my skills in python
* Be familiar with the basics of scientific computing and how to use the CSC tools available.
* I would like to learn more basics of scientific computing and I think this course can help me.
* basic knowledge of HPC and the its usage
* Good mindset and best practices for computational science. When to use a computing cluster, how to use it effectively (software design patterns for running on a cluster), what can I do to maximize my workflow?
* some basic shell scripting, how to submit jobs on computing cluster
* Parallel computing either via GPUs or multi-core processing.
* Parallelization, gpu stuff, general tips and tricks
* I would like to get familiar with scientific computing and the tools available
* some HPC tips and shorcuts
* I want to understand a bit more about computational analysis. This course seems very useful for my future career.
* How to work with the Triton Cluster and utilise it’s accessibility for my calculations, and how to effectively parallelise my code.
* Getting an introduction to the tools and, in general, into HPC
* learn to use parallel computing properly and become familiar with gpu computing.
* I attended last year, but some things changed on UH cluster so I'm hoping to make some use of the breakout room during exercises.
* Sufficient understanding of HPC to take the next practical steps myself (and to be able to indicate to others - students etc - whether they should consider HPC for their own work)
* To learn more about the computational resources available for me.
* Learn the ecosystem of scientific computing and run some jobs to gain some experience
* I want to know about latest developments and some tips.
* I am analyzing NGS data and need HPC for high through put analysis.
* More familiarity with the HPC system
* How to run R code on HPC
* I have no experience in HPC and Linux usage. I have also just basic programming skills (basically, adapting existing code scripts in R and Python to my needs). Therefore, I would like to learn how to get access to HPC and solve some general tasks there (preferably with database access and work with tabular data).
* Research Computation Techniques and Fundamentals
* Understand how HPC works and how to use it.
* Triton usage
* I think I can learn how to use the HPC effectively and efficiently. Thank you very much!
* I would like to learn scientific computing from the basic concepts
* "remote debugging with GPU, using VScode for example
* other techniques and workflows for maximizing efficiency in usage"
* Do efficient calculations on data
* Hopefully something about how hpc clusters work
* I am a beginner.
* The basics of scientific computing
* data analysis
* The cluster landscape at HU, basic of linux shell commands/ how to navigate inside the cluster
* .
* I want to work with earth system models in the future
* I am very interested in learning about parallel computing and how to exploit it best to speed up my own scripts and jobs that I run on the cluster at CSC.
* I'd like to learn about array jobs and parallelization
* What can be done with HPC and how to use it.
* I wish to learn to use HPC resources better in general
* How to better use the HPC, optimise the jobs and how to better send parallel jobs to the cluster and log the data
* I wish to learn to use HPC services better in genera
* I want to learn more about the available tools in data science.
* I would like to have a better feeling for high performance computing and how it works, especially gpus and parallelization.
* I'm interested in basics of shell scripting and maybe more about general scripting
* I am mostly interested in running Python in the cluster, say, FEM codes.
* refresh my HPC skills
* "A template for how to write a bash (.sh) script that can be called with slurm (sbatch), to carry out parallel processes.
* 
* Quick tools for parallelizing process in python. 
* 
* How to modify python (.py) scripts that are being called by slurm, so that each instance is called with different parameters."
* Data analysis tools
* Data analysis for scientific research
* I would like to introduce myself in scientific computing
* Everything listed in the description :)
* I wish to improve my data analysis and  computing skills using High Performance Computing
* improve my knowledge of scientific computing
* Scientific computing
* I’m using services and would like to get an overview what is available
* What im doing
* Along with the basics of HPC, I wish to learn the parellelisation tools.
* I know some data science techniques but would like to learn more about using high performance computing.
* I would like to gain general understanding how complicated it is to use HPC.
* Something
* General introduction of HPC. Interpreting Slurm output
* "I would like to improve my programming skills and learn how to run models on servers. 
* Thank you very much :)
* Antoine"
* "Very useful commands of linux 
* and basics of writing job scripts.
* Post data management techniques in triton to save the run time and space in triton"
* HPC
* New ways to optimize my workflow.
* I have used Triton quite long already, but I would just like to check that my skills are up-to-date, especially when it comes to data storage. I am also interested in getting access to the video recordings afterwards.
* Learn HPC from the basics
* Discover methods for scientific computing and some practical guidance on them.
* I would like to learn all that is required in order to improve models I am involved in developing and which are demanding in terms of computations. I do not have much of a background on the matter to be able to give a more specific answer.
* Tools for HPC
* I hope to get familiar with scientific computing and HPC.
* Basics about scientific computing and computational analysis of data.
* How to use triton skillfully
* To speed up my workflow with big datasets.
* I am working on developing computational models for structural modeling, so I would like to get familiar with the fundamentals of scientific computing.
* Running many jobs e.g. train model with multiple hyperparameters.
* I wish to learn the first steps to take towards doing scientific computing
* Learn how to use HPC with Linux command in a systematic way.
* I would like to learn Linux shell script to be able to work on Triton
* The triton usage
* Basics of Scientific Computing
* Not sure yet. I'll see.
* I wish to learn how to use HPC cluster, learn how to optimize my code for HPC. Learn where and when to use HPC and for what types of jobs.
* Introduction to modern tools of scientific computing and practical advice about how to take advantage of them.
* Basics of parallel and GPU computing in an HPC environment, and monitoring job efficiency.
* I would like to learn how to use computer clusters in the best possible way. I am kind of a new user, so I think I have a lot to learn in general. I used already computer clusters, but I never prepared the scripts necessary to parallelize calculations on GPUs or CPUs.
* An introduction to the HPC as I am starting to use Triton for my research
* How to run jobs via slurm, using multiple cores and nodes to run parallel jobs, GPU computing
* "Scientific computing with MATLAB,
* How to code/Ode45"
* Expand ML knowledge.
* Pretty much everything is new for me in this field so I think I will learn a lot in this course. I'm open minded.
* How to effectively utilize and manage the power of HPCs, and how to parallelize tasks.
* I wish to learn  a scientific programming language that focuses on simplicity and productivity. Scripting algorithms using proper data structures and that is used widely for computational science and computational mathematics.
* Most of all I need general information about analysis options in Aalto and how the systems are run. For example, in last summer's kick start nothing was told about how to use GUIs in Aalto's computing systems.
* I have attended this before but at that time I didn't quite need it. I would be interested to learn about it now because I am in need of computational resources and would like to know more.
* I'd like to learn some basics related to HPC so that I'd be more inclined to utilize HPC later in research.
* I want to learn more on HPC for research purposes.
* I have registered to another workshop at University of Turku and I just see this workshop properly in line with it and I am generally curious to learn more about everything on the topic.
* High Performance Computing
* How to run code (e.g. python) that takes large quantities of data as input. I work with netCDF files (climate model outputs), and it takes too much time to process those on my desktop.
* I would like to get some input and information useful for getting started with scientific computing and what it can be used for.
* I want to learn how to use Aalto's computing resources and gpu computing.
* The very basics, I have no idea whatsoever of the topic.
* basics of scientific computing
* Basics on clusters, tools that can be usefull
* 

# insights from new-triton-user survey

*Note: most of those who answered here are "junior" users with some experience on scicomp. This might bias the results as you won't get the insights of those who worked on this for 20 years, but it still has value.*

### What do you know now about scientific computing, that you wish that someone had taught you when you began as a researcher (or student)?

* everything
* TBD
* That is free; and how to use it.
* Always read the manual and the tutorials
* Use a unique organization for data structures / Use test driven development if you are building toolbox / Use git / Use available software
* That the code behind it needs to be readable (coming from a no prior-developer experience).
* Working with data frames, better parallelization (e.g. how to program pipelines with dependencies)
* How the basic system works in our computers
* Writing an optimized parallel code, using modern libraries, using version control systems
* How to google properly
* Basic use of Linux bash including scripting
* Data formats are usually the hardest part.
* I haven't really got into the subject yet
* I wish I had beein given a bit more general guidelines in the beginning of my studies, e.g. that I should learn to use the Linux shell and which programming languages or so
* ftwares will be most useful for me during my studies. Also simple things like naming of files or oganizing data in an efficient, systematic way could have been thought in a
*  more generalized frame.
* I wish I learned about this a bit sooner than just now. I think it would have benefitted me before as well
* Proper optimisation of code
* how to work in it from first step to run a code
* It should be introduced earlier on the studies. It is basically mandatory, so that should be brought up. The leap from tiny python scripts to scientific computing with larg
* e datasets is huge and quite intimidating,  especially for an undergraduate students.
* Linux terminal basics such that it is easy to get started on a cluster.
* no body told me anything when I started as researcher in Aalto but thankfully we have quite good inros how to use e.g. triton
* That it is extremely valuable and available.
* I'm more aware of the resources offered by my University and more importantly I know how to use them in my daily work. In principle this is the module system and SLURM, and
*  the fact that I always keep in my mind during development that at some point this needs to be sent for batch processing. This last concept is the greatest achievement for
* me now.
* About how to access aalto virtual machine.
* Standard shell commands (rsync, ssh, scp, awk...), installing software/packages from command line (apt-get, pip...), version control with git
* That Linux commandline is helpful for so many other things so learn it.
* Version control and commenting is very good.
* How to convert small files (csv/txt to binary formats).
* "strategies on how to pass parameters and input files to our codes and how to organized outputs.
* "
* That it is seems to be doable and there is plenty of helpful materials available :D
* debugging
* How to decently package code (autoconf, automake, CMake, ...)
* I am still just beginning as a CS student, but in previous research I would have liked to know how to use git well.
* Because of my age I never got an introduction to Linux... But it is my own fault that I haven't fixed this properly over the years.
* N/A
* Not too much.
* I don't know much, but a person in our research group will teach me
* It's all about filtering noise.
* hands on training
* Environment preparation
* It is helpful to have tutorials or opening lessons that guide step by step for fast getting stated.
* Parallel coding
* I have used HPC before.
* How to access resources in practice and use them for computing.
* Yes
* You generally need less computational power than you expect.
* "I still have no clue how this works.
* I need CERN Root and Geant4, but my laptop does not have enough RAM for that."
* That it is easily accessible and very much learnable even with low coding background.
* Linux commands and latex basics
* Student
* No, Thanks
* That parallelising your script can be as simple as running the same script multiple times with different input datasets.
* I would be absolutely desired to get it as a course at very beginning
* Programing skills, Shell scripting
* I can not name something specific, but many things I just did without understanding the processes behind it or what I was exactly doing
* How to ask the right questions, although this comes with practice.
* How to use the computing resource
* That prob you should be using Spyder.
* use version control :D
* Why Linux/Unix is so much better than Windows. And forcing me to learn Linux/UNIX
* Test driven development, Better data management practices
* Basic stuff such as installing software using conda environment
* UNIX Shell stuff
* 1) Programming can be fun! 2) One should learn Python as early as possible. 3) Fortran is being replaced by more modern programming languages, and therefore one can have a
* career in computational physics without having to work all the time with Fortran.
* Cluster computing
* I still have a feeling that I do not know enough about practicalities how to use all possible opportunities.
* Useful scripts, commands, shortcuts on Ubuntu. How to use a HPC, softwares to download, etc.
* yes
* Software development of programs which run more than a handful of seconds on local machine is annoying. If the software can only be run on remote machines and it runs for h
* ours, it is intolerable. Therefore the software must be designed so that it can be developed and tested locally, yet it must remain easily deployable and inspectable on rem
* ote machines. The deployment part remains an unsolved problem if your software uses non-trivial libraries.
* You really should write tests for your code
* How to be comfortable in the terminal (has to be figured out by each student again in my original university, but Aalto seems to have already solved this and provide a lot
* of introductory material)
* MPI!
* 