LM emptymalei

How to install CUDA / cuDNN / TensorRT on Ubuntu

Install NVIDIA drivers

Update & upgrade

sudo apt update && sudo apt upgrade

Remove previous NVIDIA installation

Setting Up Your Personal GPU Server: A Step-by-Step Guide

I've been using a GPU workstation with an RTX 4090 for almost a year now, and it's been one of the best decisions I've made. With a personal GPU server, you no longer need to rely on cloud-based GPU instances from services like RunPod or Vast.ai every time you want to run a job or try new models. The best part? No stress about recurring GPU instance costs! :-)

However, I rarely work directly on my workstation. Instead, I prefer the flexibility of accessing the GPU remotely using my MacBook, whether I'm working from different locations within my home, from a co-working space, or a cozy cafe in another part of town.

In this blog, I will walk you through the steps to configure a personal GPU Ubuntu server.

For this guide, I assume you already have a workstation running Ubuntu with a GPU and it is connected to your local network

	What is redash?
	Redash is database viewer included BI tool inside. Redash has support for querying multiple databases, including: Redshift, Google BigQuery, PostgreSQL, MySQL, Graphite, Presto, Google Spreadsheets, Cloudera Impala, Hive and custom scripts.

	Prerequisite :
	1. Install docker
	2. Install git

	git clone https://github.com/getredash/redash.git
	docker-compose -f docker-compose.production.yml run --rm server create_db
	docker-compose -f docker-compose.production.yml up

	name: Docs
	on:
	push:
	branches: [ master ]
	pull_request:
	branches: [ master ]

	jobs:
	build:
	name: Build docs

	import numpy as np
	import plotly.offline as pyo
	import plotly.graph_objs as go

	# Generate a random signal
	np.random.seed(42)
	random_signal = np.random.normal(size=100)

	# Offset the line length by the marker size to avoid overlapping
	marker_offset = 0.04