DOI Author: Miles Benton (GitHub; Twitter)Created: 2021-21-01 23:15:32Last modified: 2021-10-11 08:53:33 hackmd-github-sync-badge :::warning ATTENTION: this document is an ongoing work in progress. :::

Author: Miles Benton (GitHub; Twitter) Created: 2021-11-16 10:24:03 Last modified: 2022-08-17 10:37:17 A note on live basecalling From ONT community forum link: “Keep up” is defined as 80% of the theoretical flow cell output. e.g. MinION = 4000 kHz x 512 channels x 0.8 = 1.6 M samples/s = 160 kbases/s at 400 b/s

Author: Miles Benton (GitHub; Twitter; Gmail) Created: 2022-02-08 16:56:50 Last modified: 2022-02-11 20:24:06 Nvidia GPUs drastically accelerate the basecalling rate of Nanopore data. This is great, but not all GPUs are built equally, meaning that sometimes you'll need to tweak specific parameters to either increase performance, or on the other side of the coin, tune down parameters so that a lower spec'd card can work. Some examples of this: you have a card with more than 8GB of RAM (such as a RTX3080, RTX3090, A5000) and you want to get more basecalling performance from high accuracy (HAC) and super accuracy (SUP) models. you have a card with less than 8GB of RAM (such as GTX1660, RTX2060, RTX3050) and you want to be able to use Guppy for live basecalling or running the HAC/SUP models without running into CUDA memory issues. For some time I've been meaning to put together something more structured around how I go about tuning Guppy parameters to get the most out of particular GPUs for the Nanopore basecalling work that we do. This document is an attempt at that.

Author: Miles Benton (GitHub; Twitter) Created: 2021-07-16 20:15:56 Last modified: 2022-01-19 13:54:40 For some time I've been wanting to put together my thoughts around price/performance ratios of GPUs. I've been thinking that there must be a "sweet spot" for users that are wanting to run a single MinION Mk1b and have access to things such as adaptive sampling and live basecalling with FAST/HAC models. Bonus points if it has decent retrospective basecalling performance. I've been very fortunate recently in terms of being provided with a range of hardware that has allowed me to start exploring this. So I wanted to create some notes to provide the information back to the community, for any users that are interested and may be in the market for a GPU, or people that just want an idea of the type of performance you can expect from various GPU models. I'm hoping that this becomes a dynamic document and will evolve with time. For now I want to report on a comparison I was able to perform using an external GPU enclosure (eGPU) paired with two of the Nvidia Ampere cards, a RTX3060 and a RTX3080Ti. These are two cards aimed at gaming, one at the 'lower' end (RTX3060) the other very much at the higher end (RTX3080Ti). Obviously this is reflected in the price with the RTX3060 being ~$1000 NZD and the RTX3080Ti ~$3000.

Author: Miles Benton (GitHub; Twitter) Created: 2021-08-30 08:15:02 Last modified: 2021-08-31 20:49:50 :::warning WARNING: please ensure you are comfortable with the command line, and are willing to accept any and all responsibility for potential issues that may arise. All efforts have been made to ensure this is as safe and easy to revert if needed, but the author takes no responsibility if things go pear shaped or don't work. Below there be dragons (potentially)! ::: This is a set of notes for getting MinKNOW running with live GPU basecalling on a computer running Ubuntu 21.04 (or a base of 21.04, such as Pop!_OS).

Author: Miles Benton (GitHub; Twitter) Created: 2021-06-16 21:05:32 Last modified: 2021-06-21 11:24:06 :::warning WARNING: this is still very much 'experimental' in terms of the process and packages that are available. I will highlight throughout this section exactly which software and/or drivers are currently in beta - be warned it's pretty much everything. ::: Foreward This is documentation of my notes and experiences getting a brand new laptop running Windows 10 to perform GPU basecalling via Windows Subsystem for Linux 2 (WSL2).

There are many ways to create borders around different objects in Inkscape. Potentially the 'easiest' is a sort of cheat if you will. We are going to use the rectangle tool and play with transparency to get what we want. Here is a step by step to follow along. import your object (graph, figure, table, text, ...) into Inkscape: create a box around the object you want to give a border, we use the rectangle tool (you can draw over top of the thing you want to put a border around, we'll tidy up later): we can now create a border around our box/rectangle using the stroke function: open 'Fill and Stroke' menu:

Coolors is a great website that allows you to interactively create a beautiful and colourblind friendly colour palette for your project. Here's a quick step by step guide to exporting a palette and importing it into Inkscape. Go to Coolors and create a palette: Click the 'Export' button up in the top right: You should be presented with options (see below), select 'SVG': Save the palette file (svg) to your computer.