Introduction

I have been interested in trying out astrophysics-related simulations for some time, and had been checking out ENZO, GADGET, GIZMO, and others. I happened to know Athena, and when I looked into it, I found that Associate Professor Kengo Tomita of Tohoku University maintains a Japanese page and has some information in Japanese, so I decided to give it a try.

Here, I summarize the process of installing and running the tutorial, and post it.

Motivation

In this article, I ended on a negative note about quantization, but after a little research I reconsidered it as an interesting area and experimented with quantization, which I I summarize it here.

Motivation

Looking back on the year 2023, it was a year in which many Japanese LLMs (Large Language Models) were released. I have tried to run some of them in my home environment, so I will summarize them here.

Introduction

With Try Horovod in Docker, you can now use Horovod in your own environment (on-premises) and in a Docker environment. The next thing to do is to modify the training code running on a single server to apply it to distributed training using Horovod! For starters, I modified a relatively simple CNN code to allow distributed learning using Horovod, which is summarized in the following article.

Motivation

I have been interested in Distributed Training for about a year. I have been experimenting with a distributed learning framework called Horovod on multiple TITAN-V-capable machines. I finally got a distributed training sample working, so I am posting it here.

Introduction

In May of this year, I posted an article Building Rootless Docker, but for some reason I decided to uninstall rootless docker. The following is a summary of the uninstallation procedure. I will post the details of the circumstances that led to the uninstallation of rootless docker later.

Introduction

Over a month ago, I became interested in NVIDIA Modulus at the How to Speed Up Simulation with AI Surrogate Models? seminar I attended, I became interested in NVIDIA Modulus, so I bought the book and started studying it. As a prerequisite for future study of Modulus, I installed Modulus in my environment, so I summarized the installation process as “Introduction to PINNs”.

Motivation

I wanted to try out a large-scale language model (LLM) for Japanese, so I used rinna, which was released in May. To save installation time, I ran rinna under a docker container environment.

I ran into some problems in doing so, which are summarized below.

Introduction

It has been a year since Ubuntu 22.04 LTS Jammy Jellyfish was released, and I decided to switch from my previous 20.04 to 22.04, thinking that I would be able to get used to the various software and other features.

I installed ubuntu 22.04 Japanese Remix on several workstations so that I can use Japanese easily. I have gotten a bit stuck trying to install ubuntu 22.04 on a NVIDIA GPU-equipped workstation, so here is the situation and how I responded.

Motivation

In a previous post I summarized how to start a docker container in user mode.

When using multiple PCs (WorkStation, hereafter WS), it is necessary to consider how to realize a mechanism to share containers among multiple WS. In the case of singularity, we could store sif files on an NFS server and use them from other WS.

In case of docker, I decided to build a registry server, thinking that I could set up a private registry in my home network and operate it.