Difference between revisions of "Applications/guppy"

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Using the GPU as an accelerator will make the analysis considerably faster (on large data sets). For small runs, the CPU version is recommended and probably faster by removing the GPU overhead.
 
Using the GPU as an accelerator will make the analysis considerably faster (on large data sets). For small runs, the CPU version is recommended and probably faster by removing the GPU overhead.
  
Important: guppy/gpu (GPU version) requires to compute level of six or above, see examples below.
+
 
  
 
===Batch example===
 
===Batch example===
 
This uses 2 GPUs presently on GPU05 ('''compute level is high than 6''') which is required by guppy's minimum requirement.
 
  
 
<pre>
 
<pre>
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#SBATCH -J guppy.job
 
#SBATCH -J guppy.job
 
#SBATCH --exclusive
 
#SBATCH --exclusive
#SBATCH -o gpu05.%j.out
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#SBATCH -o gpu.%j.out
#SBATCH -e gpu05.%j.err
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#SBATCH -e gpu.%j.err
#SBATCH -p gpu05
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#SBATCH -p gpu
#SBATCH --gres=gpu:tesla:2
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#SBATCH --gres=gpu
 
#SBATCH --exclusive
 
#SBATCH --exclusive
  
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* NVidia A40 is at least 6.0 (GPU01 to GPU04)
 
* NVidia A40 is at least 6.0 (GPU01 to GPU04)
 
* NVidia P100 is 6.0 (GPU05)
 
* NVidia P100 is 6.0 (GPU05)
 
  
  

Revision as of 15:17, 13 December 2022

Application Details

  • Description: Local accelerated base calling for Nanopore data.
  • Version: guppy 3.1.5 to 6.4.2
  • Modules: guppy/cpu/3.1.5 (CPU) to guppy/cpu/6.4.2 (CPU)
  • Modules: guppy/gpu/3.1.5 (GPU) to guppy/gpu/6.4.2 (GPU)
  • Licence: Free, open-source
  • Note: guppy version 3 will be removed from service soon

Usage Examples

Using the GPU as an accelerator will make the analysis considerably faster (on large data sets). For small runs, the CPU version is recommended and probably faster by removing the GPU overhead.


Batch example

#!/bin/bash
#SBATCH -J guppy.job
#SBATCH --exclusive
#SBATCH -o gpu.%j.out
#SBATCH -e gpu.%j.err
#SBATCH -p gpu
#SBATCH --gres=gpu
#SBATCH --exclusive

module purge
module load cuda/10.1.168
module load guppy/gpu/6.4.2

guppy_basecaller --input_path /home/user/folderIN --save_path /home/user/folderOUT --flowcell FLO-MIN106 --kit SQK-RPB004 --min_qscore 7 --qscore_filtering -x cuda:0 cuda:1

Compute capability

For applications that require this information:

  • NVidia A40 is at least 6.0 (GPU01 to GPU04)
  • NVidia P100 is 6.0 (GPU05)


Further Information





Modules | Main Page | Further Topics