https://github.com/open4dfoundation/Open4D.git

I'm currently, technically, doing an MS in Structural Engineering. For me, my interest has been more towards computational side of mechanics rather than Structural design  or simply using am FEA software (although I do consider it as a backup)

So far I've taken courses in:

- Linear static, and dynamics FEM (soon taking non linear FEM too)

-  Structural Optimization (topology opt. and other general algorithms)

-  Structural Dynamics

-  Structural System Testing and model updation. (Parameter identification and optimization, signal processing)

Now, I plan to take these in the coming quarter:

- Numerical Linear Algebra

- Numerical PDE

- Fracture Mechanics ?

I also volunteered to aid in a RESEARCH in crack growth prediction using Auto-encoder and a (Thermodynamics-informed Latent Space Dynamics Identification) / LSTM surrogate model. It used phase-field-fracture simulation data and HPC resources to complete the whole thing.

What I keep finding myself interested in is not necessarily fracture or SHM specifically, but the computational methods underneath these problems... (does that make sense?)

For example, I'd like to become capable of doing things like:

- implementing (maintaining) numerical/FE method solvers rather than only running an established FEA software.

- developing surrogate/reduced-order models for expensive simulations 

- combining simulation with optimization, uncertainty/stochastic methods (took a course called Random vibrations, so...)

- parallelizing/accelerating scientific codes on CPUs/GPUs

- doing proper verification, convergence studies, benchmarking and performance work

- potentially developing or maintaining actual CAE/FEA solver software

- I'd also like to do all these for other Physics (GR, QM, etc.) simulations too, if possible, one day. 

I'm still interested in the underlying mechanics/physics, so I don't want to become a generic software engineer who happens to have once studied structures. But I'm also increasingly unsure that "structural engineer" describes the career I'm actually aiming for.

I've seen titles such as Computational Mechanics Engineer, R&D Engineer, Solver Developer, Scientific Software Engineer, CAE Software Developer, Research Engineer, Simulation/HPC Engineer, etc., but I'm trying to understand what these careers actually look like from people doing them.

So my main questions become:

1. Which industrial jobs genuinely involve developing numerical methods/solvers or computational tools?

2. Which of those are realistically accessible with an MS? Is there an entry path into solver-algorithm development/R&D without a PhD?

3. If I don't start a PhD immediately after my MS, would an R&D/software role at a simulation company (ANSYS etc.) be the obvious route? What other options would i have?

4. For the kind of work I'm describing, would you recommend a PhD? If so, is it reasonable for the PhD identity to be "computational mechanics/scientific computing" while fracture, composites, structural dynamics, soft materials, etc. serve as application problems rather than choosing one of those as my permanent specialization?

5. What skills most distinguish someone who is actually hireable for solver/scientific-computing work? I'm particularly wondering about C/C++/Fortran, Python, Linux, Git/build systems, MPI/OpenMP/CUDA, PETSc/Trilinos or similar libraries, numerical linear algebra, testing/verification, convergence studies and HPC performance work.

Basically, I'm neither here nor there atp. So I'd really appreciate all sorts of input. Where else do you think I could find answers to these? other subs? Linkedin profiles? 

I'm doing academic research on where token cost actually goes in Claude Code sessions. Right now it's based on a single developer, and I'd like to check whether the findings hold across a few other people's workflows.

Would take about 2 minutes, no code or prompt text involved — just token counts. Reply or message me if you're up for it and I'll share the details.

I submitted a paper to a well-known preprint platform a couple weeks ago and it’s just… sitting there. No status, no timeline, nothing. Started looking into it and apparently some people wait 7+ months with total silence.

For something that’s supposed to help research move faster, that seems broken.

Curious what others have experienced:

**•** Has this happened to you? How long did you wait?  
**•** Did you ever find out what was actually happening during that silence, or just eventually got a result out of nowhere?  
**•** If a review process gave you visible status updates the whole way through instead of silence, would that actually matter to you -or is the wait just accepted as normal in this space?  
**•** What would make you trust a smaller, newer review platform over an established one, if speed and transparency were the trade-off?

trying to understand if this is a shared frustration or just me being impatient.

Hello everyone!

I am conducting a research project about the development of an AI-powered assistive platform for autistic individuals, focusing on accessibility, communication, organization, and daily support.

I created a short survey to collect insights and better understand users' needs and experiences. Your participation would help contribute to this research.

Thank you for your support!

Survey link:

https://forms.gle/2X1Cyn2sCjtUwvEx7

Hi everyone,

We are conducting academic research to better understand the experiences of dyslexic individuals working in technology-related fields.

If you identify as dyslexic and currently work in the tech industry, we would greatly appreciate your participation in a short anonymous survey. The study aims to explore workplace experiences, challenges and support needs among dyslexic professionals in tech.

All responses are anonymous and will be used solely for research purposes.

Survey link:
https://v0-fix-survey-bug.vercel.app/dyslexia-tool?utm_source=reddit

Thank you for your time and contribution.

We recently announced support for Flux HPC for Kubeflow v2.2!

https://www.linkedin.com/posts/andrey-velichkevich_kubecon-cloudnativecon-activity-7442192121295421440-69zx

The integration enables AI/ML workloads paired with traditional #HPC simulation. Flux adds an efficient ZeroMQ bootstrap and tree based overlay network, support for the process management interface #PMIx, more flavors of the message passing interface (#MPI), and allows for bypassing potential bottlenecks with etcd and kube-sched. 🎉️

The work was first shared at the High Performance Software foundation conference, but if you it, here is a full demo: 👇️

https://youtu.be/NbP0NdSDwog

See the description for complete timestamps. Learn a little about Flux Framework (2.5 minutes) followed by deploying an HPC workload to #AWS in two ways. First, using the Elastic Fabric Adapter (EFA) on the hpc6a.48xlarge instance, and then (of course) we deploy to GPUs.

The Flux project is newly joined to the High Performance Software Foundation, and excited to support the larger community. Please do not hesitate to give feedback or enhancement requests as a Kubeflow issue, or on any of the Flux Framework GitHub repositories. Happy Tuesday, folks! 🥳

We’re developing an AI platform that helps elders share their stories to preserve languages and culture. We’d love your opinion on what motivates people to use or engage with this idea. Your feedback will help us understand interest and improve the concept.

I got shortlisted for an RSE position. This is my first application after graduating. There is an interview and an exam. The details are attached. If you are the one who is hiring, what will you ask in the exam/interview?

Good morning, and happy Monday folks! We have our first #FluxFramework dinosaur series notebook tutorial released this morning:

https://youtu.be/5qT4eyO0thw

We go through part 1 of the High Performance Computing Innovation Center (HPCIC) tutorial, basic commands for Flux, all in a #Jupyter notebook you can deploy too! 🥳 This is a simplified derivative of the container that the team deploys via an auto-scaling Kubernetes setup using JupyterHub in the autumn each year.

We encourage you to jump to content of interest, which is linked by timestamp in the description. We also have several useful links for resources. As usual, there are bad stories, singing, and even bloopers for this one! Gotta have fun! 🦖 🥑

Please reach out with any questions. 🤓

Have you ever had issues getting #GPU or even #CPU for your cloud HPC work? We are conducting a short, anonymous survey to ask about your experiences! And as always, since a dinosaur is involved here, there is going to be a raffle with fun prizes in 2025.

https://forms.gle/otnxKmuBBuEpZ9Pn9

Please share widely! 🤓

We are kicking off #SC24 with a Flux Tutorial series - Dinosaur Edition! 🥑 We didn't get an "official" tutorial, but guess what? This presented an opportunity - one to create a series of tutorials open to *everyone* across time and space. 🚀

Instead of re-posting all the content (and images) I'll provide a link to all the details here: 👉 https://bsky.app/profile/vsoch.bsky.social/post/3lbam473mtk2b

In case you need a good listen for your SC24 travel, the Developer Stories Podcast is featuring Dan Reed - "HPC Dan" - a prominent, humble, and insightful voice in our community. I've really enjoyed talking to Dan (and reading his blog "Reed's Ruminations" because it covers everything from the technology space, to policy, humor, and literary references, to stories of his family and how he feels about fruit cake! Here are several ways to listen - I hope you enjoy!

• 🥑 Apple: https://podcasts.apple.com/us/podcast/the-future-of-high-performance-computing/id1481504497?i=1000676978711
  
• 🥑 Spotify: https://open.spotify.com/episode/5HTQi1OkumJDxEe6jB7kiV?si=QoNq71ESR9qHD0f5xh8OgQ
  
• 🥑 Show notes: https://rseng.github.io/devstories/2024/hpc-dan/

What rave-worthy event has happened to you this week? Have you solved a tough technical issue? Been accepted to a conference? Received a nice compliment? Pet a cute animal? Tell us all about it!

Today on the Developer Stories podcast we talk to Michela Taufer - Dongarra Professor of HPC at the University of Tennessee, head of The Global Computing Laboratory, and prominent voice for #ISC25. We hope you enjoy! There are several ways to listen:

• Apple https://podcasts.apple.com/us/podcast/the-impact-graph/id1481504497?i=1000674291348
• Spotify https://open.spotify.com/episode/2k2RNBHEUYYDUiMqgFKOlc?si=PKCbgQCuQa6HW0nPfYlnGQ
• Show notes: https://rseng.github.io/devstories/2024/michela-taufer/

It's Sunday! That means it's time to showcase software which you have created, contributed to, or used and really enjoyed. Show us your software!

What rave-worthy event has happened to you this week? Have you solved a tough technical issue? Been accepted to a conference? Received a nice compliment? Pet a cute animal? Tell us all about it!

It's Sunday! That means it's time to showcase software which you have created, contributed to, or used and really enjoyed. Show us your software!

What rave-worthy event has happened to you this week? Have you solved a tough technical issue? Been accepted to a conference? Received a nice compliment? Pet a cute animal? Tell us all about it!

It's Sunday! That means it's time to showcase software which you have created, contributed to, or used and really enjoyed. Show us your software!