kmhofmann

Installing the NVIDIA driver, CUDA and cuDNN on Linux (Ubuntu 20.04)

This is a companion piece to my instructions on building TensorFlow from source. In particular, the aim is to install the following pieces of software

• NVIDIA graphics card driver (v450.57)
• CUDA (v11.0.2)
• cuDNN (v8.0.2.39)

on an Ubuntu Linux system, in particular Ubuntu 20.04.

zmwangx

#!/usr/bin/env python3

import sys

import eventlet
eventlet.monkey_patch(socket=True)
from eventlet.timeout import Timeout
import requests

hackersoup

;; Hardware IDs
HWID_LEGS     equ 0x1
HWID_LASER    equ 0x2
HWID_LIDAR    equ 0x3
HWID_KEYBOARD equ 0x4
HWID_DRILL    equ 0x5
HWID_INV      equ 0x6
HWID_RNG      equ 0x7
HWID_CLOCK    equ 0x8
HWID_HOLO     equ 0x9

kmhofmann

Building TensorFlow from source (TF 2.3.0, Ubuntu 20.04)

Why build from source?

The official instructions on installing TensorFlow are here: https://www.tensorflow.org/install. If you want to install TensorFlow just using pip, you are running a supported Ubuntu LTS distribution, and you're happy to install the respective tested CUDA versions (which often are outdated), by all means go ahead. A good alternative may be to run a Docker image.

I am usually unhappy with installing what in effect are pre-built binaries. These binaries are often not compatible with the Ubuntu version I am running, the CUDA version that I have installed, and so on. Furthermore, they may be slower than binaries optimized for the target architecture, since certain instructions are not being used (e.g. AVX2, FMA).

So installing TensorFlow from source becomes a necessity. The official instructions on building TensorFlow from source are here: ht