Unlike the interactive Graphical User Interface, there is also a CLI for use on headless machines or HPC clusters, when local memory requirements just don’t cut it. Here we go over some of the basic functionality:

IPython

Although the script works through normal python or Jupyter notebooks, the most intuitive way to explore data is through the IPython shell. This allows the user to run the script, and then manually manipulate the data afterwards.

Viewing the arguments

There are a number of available arguments, and the easiest way to view these is by using the --help option

A quickstart anaconda environment cheatsheet for everyday use.

Creating an Environment

We choose to create an environment named myenv

Within The Conda Folder

conda create --name myenv

Custom Location

A custom location (e.g. this directory under the name myenv)

conda create --prefix ./myenv python=3.7 --yes;

Cloning an Existing Env

conda create --name myenv --clone env2clone

Activating / Deactivating an Environment

Listing all environments

conda info --envs

To activate an environment

conda activate myenv

To activate a custom located environment

Activating an environment at location ./myenv

conda activate ./myenv

To deactivate an environment

conda deactivate

Removing and existing environment

conda env remove --name myenv

Exporting/Importing Environments

Saving your existing environment dependencies

conda env export > environment.yml

If we want to avoid version numbers we can use the following command instead:

conda env export | cut -f 1 -d '=' > environment.yml

Creating a new environment from a YAML file

conda env create -f environment.yml

Updating a conda env using a YAML file

conda…

With the introduction of two-factor authentication, we are now required to change the way we access our repositories. There are now two main methods to upload to Github: using ssh keys or access tokens. This page describes the latter.

Creating a token

1. Click on your user icon (top-right)
2. Select Settings
3. From the left-hand menu, select Developer Settings
4. Personal Access Tokens
5. Right-top: Generate New Token

Copy and SAVE the token, you will not get to view it again without generating a new one!

Storing the token

Caching for a TEMPORARY period in time

If we wish to store our token for a fixed period in time we may cache it with a predefined timeout.

…

How to create a fully customised colour mapping within matplotlib.

Problem

Our data is split into non-uniform categories, where a linear colour bar will be inefficient. In this tutorial, we cover how to create a custom colourmap with colours matching bins of our chosen sizes.

Solution: Discrete Colour Bars

We start by importing the required packages

import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np

Next, we decide on our colours:

colours = ['#ffbe0b', '#fb5607', '#ff006e', '#8338ec', '#3a86ff']

And the bin sizes which correspond to them. — e.g. {0 → .3}, {0.3 → .7 } etc… I have intentionally chosen non-uniform bins.

…

Just some notes on getting started.

What is Bede?

Bede is the N8’s Tier 2 Power and GPU-based high-performance computing (HPC) platform.

Resources available

32x Main GPU nodes, each node (IBM AC922)

• 512GB DDR4 RAM
• 2x IBM POWER9 CPUs (and two NUMA nodes), with
• 4x NVIDIA V100 GPUs (2 per CPU)
• Each CPU is connected to its two GPUs via high-bandwidth, low-latency NVLink interconnects (helps if you need to move lots of data to/from GPU memory)

4x Inferencing Nodes:

• Equipped with T4 GPUs for inference tasks.

Other

• 2x Visualisation nodes
• 2x Login nodes

Filestores

The filestore layout is similar to that of the ARC system. …

Notes on how to set up an interactive GPU session for computation on the Leeds System.

Start a session

Arc4

qrsh -l h_rt=2:0:0,coproc_v100=1,h_vmem=8G -pty y bash

A single V100 card, 10 CPU cores and 48GB system memory (one quarter of the available resource on a V100 node)

Arc3

qrsh -l h_rt=2:0:0,coproc_k80=1 -pty y bash

A single K80 card, 12 CPU cores and 64GB system memory (half the available resource on a K80 node)

or

qrsh -l h_rt=2:0:0,coproc_p_100=1 -pty y bash

A single P100 card, 6 CPU cores and 64GB system memory (one quarter of the available resource on a P100 node)

Check the Card you Have Been Allocated

module load cudanvidia-smi…

Sometimes we require multiple modules all of which communicate using the I2C channel. In this post, we discuss how to do exactly that using available GPIO pins.

Setup

We begin with installing the required libraries,

sudo apt-get install -y python-smbus i2c-tools

followed by enabling I2C using the advanced tab within raspi config. I this does not make sense, have google ‘using I2C on Raspberry Pi’ and the device you are trying to connect. Make sure you can connect this successfully before continuing.

Conventional I2C ports

Generally, to set up we use pins 3 and 4 (see the diagram below) to connect a device. In…

You have a suite you wish to run, but need to constrain it such that it can run on your allocated queues — this guide explains how to break it into segments which allow you to do so.

Accessing the run initialisation panel through rose

The run I am using is u-ca218 . First, you need to open the rose editor and navigate to suite conf → run initialisation and cycling using the menu on the left.

Here you will have a set of options including an initialisation file, calendar and other information.