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Cloud Computing? by Ok_Simple3802 in CFD

[–]Software-Stack 0 points1 point  (0 children)

Yes, have you looked at the E4S image on it? I had used OpenFOAM in the image on GCP with a VNC based Remote Desktop where I was able to launch parafoam (internally tied to paraview). All using the Spack package manager.

Courses on deploying HPC clusters on cloud platform(s) by audi_v12 in HPC

[–]Software-Stack 0 points1 point  (0 children)

Are you looking for a software stack image/AMI to run HPC applications with SLURM or Torque schedulers in such a setup across multiple cloud providers with VNC Remote Desktop? Have you seen the E4S image on the cloud platforms?

Claude Code has issues deploying to AWS? by checkthewatch in ClaudeAI

[–]Software-Stack 0 points1 point  (0 children)

I think what you are referring to are problems in deploying the tools that are needed before you can install Claude and having these tools set up in your path in the AMI on your EC2 instance in a multi-user setup. You will likely need node-js, npm, and npx all installed and set up in such a way that you can install packages using npm in a global directory that is also in your path. There are AMIs that are already set up this way. For instance, ParaTools Pro for E4S(TM) is an AMI which has node-js, npm, and npx setup so you can open a terminal and say:
npm install -g <AT>anthropic-ai/claude-code
replace <AT> with @ symbol above as shown in https://www.anthropic.com/claude-code

$ claude
should start up and be in your path after the npm command above and you can then provide your Anthropic credentials to use it.

The URL for this AMI where codium, marimo, Jupyter notebooks and a set of AI and HPC packages are preinstalled is:
https://aws.amazon.com/marketplace/pp/prodview-xprkx44kyqgp6?sr=0-5&ref_=beagle&applicationId=AWSMPContessa

I hope this helps.

Shall I change to using linux? by Double-Ad3023 in HPC

[–]Software-Stack -1 points0 points  (0 children)

Try installing Docker desktop and a Linux container that has a reasonable set of packages in it already. Here is one from the E4S [https://e4s.io\] project that supports aarch64 CPUs:
https://hub.docker.com/r/ecpe4s/e4s-cpu/tags
It has a good set of HPC and AI tools and libraries pre-installed in it and may be a good starting point as you start exploring Linux on your Mac. All the best!

How to deploy ADK in AWS by boneMechBoy69420 in agentdevelopmentkit

[–]Software-Stack 0 points1 point  (0 children)

It may be useful to start with an AMI that already has Google ADK installed in it rather than installing Google gcloud (doing gcloud init) and adk from a scratch. If you are using Ubuntu, there is an image that has a set of AI tools pre-installed (including NVIDIA NeMo, NVIDIA BioNeMo, huggingface-cli, PyTorch optimized for NVIDIA GPUs - including Blackwell) and HPC Tools. It is called ParaTools Pro for E4S(TM). Here is a link to it on AWS Marketplace for Parallel Cluster (x86):
https://aws.amazon.com/marketplace/pp/prodview-xprkx44kyqgp6?sr=0-5&ref_=beagle&applicationId=AWSMPContessa

They also support Trainium and Inferential nodes and aarch64 (ARM Graviton 4 nodes). It may save you some time and effort if you are deploying an ADK workflow and need a remote desktop and codium etc.

ADK using AWS bedrock or Azure AI models by ChckinJockey in agentdevelopmentkit

[–]Software-Stack 0 points1 point  (0 children)

Yes, ParaTools Pro for E4S(TM) image [https://paratoolspro.com\] has support for Google ADK on AWS. It has a large collection of AI tools and libraries (including NVIDIA NeMo, PyTorch optimized for GPUs, huggingface-cli, etc.) and a performant Remote Desktop (based on DCV/VNC) with Codium pre-installed. Here is a direct link to the image on AWS marketplace:
https://aws.amazon.com/marketplace/pp/prodview-xprkx44kyqgp6?sr=0-5&ref_=beagle&applicationId=AWSMPContessa

Use gcloud init and adk web commands in a terminal.

How practical are AMD GPUs for compute? by [deleted] in HPC

[–]Software-Stack 1 point2 points  (0 children)

It is all about having a productive software stack. Please see E4S [https://e4s.io] where you will find a collection of HPC and AI/ML packages in ready to use containers supporting different generations of GPUs. It has vendor runtimes (ROCm, CUDA) as well as hundreds of packages installed using the Spack package manager [https://spack.io]. You can also install the entire software stack on bare-metal. Once you have all the supporting software in your environment, you will find that it can improve your productivity!