pangyuteng

GPU Support For Docker Swarm

Docker compose has nice support for GPUs, K8s has moved their cluster-wide GPU scheduler from experimental to stable status. Docker swarm has yet to support the device option used in docker compose so the mechanisms for supporting GPUs on swarm are a bit more open-ended.

Basic documentation

NVIDIA container runtime for docker. The runtime is no longer required to run GPU support with the docker cli or compose; however, it appears necessary so that one can set Default Runtime: nvidia for swarm mode.
docker compose GPU support
Good GitHub Gist Reference for an overview on Swarm with GPUs. It is a bit dated, but has good links and conversation.
[Miscellaneous Opt

Moved to nostr-resources.com

DNAT with iptables over wireguard hosted on a VPS to host services behind a firewall/GNAT.

This is a short description of how to host services, using STORJ node as an example, on a host behind GNAT, or otherwise restrictive firewall, by forwarding packets through WireGuard endpoint on a relatively fast nearby VPS. This is not specific to Storj, and can be adopted to hosting other services.

As an example we will use an Oracle Cloud instance. Free tier still provides 10TB of monthly traffic that is sufficient for most node operators. Just make sure to create an account in a closest datacenter to minimize extra latency.

Notes on configuring the cloud instance

Create the oracle compute instance (ideally, Ampere, because they are awesome, but if that is not availabe, any other will do too).
Pick any OS you prefer, here we'll describe Ubuntu, as a most popular one.

# Resize the file system in UI, under VM -> Hardware -> Click on the disk to resize, click "Resize disk" button

# Confirm increase in disk space (1TB in my case)
$ lsblk
NAME                      MAJ:MIN RM  SIZE RO TYPE MOUNTPOINT
sda                         8:0    0    1T  0 disk
├─sda1                      8:1    0    1M  0 part
├─sda2                      8:2    0    1G  0 part /boot
└─sda3                      8:3    0    1T  0 part

Setting up a Docker Swarm with GPUs

Installing Docker

Official instructions.

Add yourself to the docker group to be able to run containers as non-root (see Post-install steps for Linux).

Lecture 1: Introduction to Research — [📝Lecture Notebooks] [▶️Video]
Lecture 2: Introduction to Python — [📝Lecture Notebooks] [▶️Video]
Lecture 3: Introduction to NumPy — [📝Lecture Notebooks] [▶️Video]
Lecture 4: Introduction to pandas — [📝Lecture Notebooks] [▶️Video]
Lecture 5: Plotting Data — [📝Lecture Notebooks] [[▶️Vide

Python version of the MATLAB code in this Stack Overflow post: http://stackoverflow.com/a/18648210/97160

The example shows how to determine the best-fit plane/surface (1st or higher order polynomial) over a set of three-dimensional points.

Implemented in Python + NumPy + SciPy + matplotlib.

	# Solution based on https://stackoverflow.com/a/51785735/278836
	import tensorflow as tf

	def extract_patches(images):
	return tf.image.extract_patches(
	images,
	(1, 3, 3, 1),
	(1, 1, 1, 1),
	(1, 1, 1, 1),
	padding="VALID")

	{
	"Version":"2012-10-17",
	"Statement":[
	{
	"Sid":"PublicRead",
	"Effect":"Allow",
	"Principal": "*",
	"Action":["s3:GetObject","s3:GetObjectVersion"],
	"Resource":["arn:aws:s3:::YOUR_BUCKET_NAME_GOES_HERE/*"]
	}

	import asyncio
	import psycopg2

	# dbname should be the same for the notifying process
	conn = psycopg2.connect(host="localhost", dbname="example", user="example", password="example")
	conn.set_isolation_level(psycopg2.extensions.ISOLATION_LEVEL_AUTOCOMMIT)

	cursor = conn.cursor()
	cursor.execute(f"LISTEN match_updates;")