[web] portal.biohpc.swmed.edu [email] biohpc-help ......apr 11, 2018  · cloud services - web based...

Interactive Environments & Data Exploration

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[web] portal.biohpc.swmed.edu

[email] biohpc-help@utsouthwestern.edu

Updated for 2018-04-11

Why Interactive Environments

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• Debugging

• Visualization

• Scripts/command generator

• Submit job directly to cluster without writing SLURM scripts

• Dedicated node for web services

• And more ..

Interactive sessions with BioHPC

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Reserve Session with command• srun• remoteGPU/remoteGUI

Cloud Services• Web based Visualization• Web Desktop

BioHPC On-Demand• DIGITS• Jupyter• Rstudio• BisQue (coming soon)

Reserve Session with command - srun

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srun --partition=super --pty --time=00:10:00 /bin/bash

srun create a resource allocation --partition select interactive partition--pty run task zero in pseudo terminal mode--time setup time limit/bin/bash gives you a pseudo terminal that runs bash

Reserve Session with command - srun

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Reserve Session with command – remoteGPU/remoteGUI

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@nucleus005(login node), TurboVNC Version 2.1.1Virtual Network Computing-is a remote display system that allows you to view and interact with a desktop environment running on a remote computer-provides high-speed solution for remotely displaying image-intensive applications over all types of networks

Reserve Session with command – remoteGPU/remoteGUI

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First, setup your VNC password with the command:

vncpasswd

• Primary VNC Password• Optional view-only password

• Password file saved at ~/.vnc/passwd• Password has to be longer than 5 characters

Reserve Session with command – remoteGPU/remoteGUI

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How to request?

• remoteGUI: super partition • remoteGPU: GPU partition• 20 hours time limit

Need more time? Send extension request along with JobId to BioHPC-help

How to access?

VNC server: nucleus.biohpc.swmed.edu:30829

Nucleus082

Cloud Services - Web based Visualization

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Web based visualization access: https://portal.biohpc.swmed.edu/terminal/webgui/

• WebGUI/WebGUI256reserve a CPU node

• WebGPU/WebGPUv1reserve a GPU node, good for ImageJ, Amira, stand-alone paraview or compile your CUDA

codestep 1: add visualization software as a modulestep 2: vglrun <software name>

Cloud Services - Web based Visualization

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• WebGUI 312 nodes available from partition super & 32GB, Minimum 32GB RAM

• WebGUI256 126 nodes available from partition 256GB & 256GBv1, Minimum

256GB RAM

• WebGPU 20 nodes available from partition GPU, Minimum 1 GPU card, Tesla

K20/K40 or 2 Tesla P100 cards

• WebGPUv1 12 nodes available from partition GPUv1, 2 Tesla P100 GPU cards

• WebWinDCV 20 nodes available from partition GPU, Virtual windows environment

(32 cores, 192GB RAM) running on a GPU node

Cloud Services - Web based Visualization (webGUI - directly submitting job to cluster)

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PEET used in conjunction with IMODeTomo is IMOD’s GUI interface

Steps:

Step 1: processchunks (broken up job into "chunks“, each for a single cpu.)Step 2: salloct -> return JobIDStep 3: srun with JobID queuechunks (from the initial processchunks command)Step 4: clean up allocation

Required module version:peet/1.11.0-alpha(will load imod/4.8.50-beta as well)

eTomoIMOD/PEET

Cloud Services - Web based Visualization (webGUI - directly submitting job to cluster)

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Queue Max # CPUs #CPUs / NODE

128 GB 16*16=256 16

256 GB 24*16=256 24

384 GB 16*2=32 16

super 16*16=256 16

GPU 16*2=32 16

submit directly from eTomo GUI interface

Cloud Services - Web based Visualization (webGUI – 32 GB partition)

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What if you’ve been assigned to a 32GB partition?

How do I know?$ sinfo -p 32GBPARTITION AVAIL TIMELIMIT NODES STATE NODELIST32GB up infinite 1 drain NucleusA01332GB up infinite 9 alloc NucleusA[003,006-007,014,077-081]32GB up infinite 70 idle NucleusA[002,004-005,008-012,015-076]

How to reduce memory reservation for applications (e.g: ImageJ)?ImageJ --mem 16g

Cloud Services - Web based Visualization (webGPU - 3D rendering)

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Cloud Services - Web based Visualization (webGPUv1 - processing with multiple GPUs)

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@GUP nodemodule add relion/intel/openmpi/cuda80/2.0-betaexport VISIBLE_CUDA_DEVICES=“0,1”vglrun relion

Specify GPU info

Cloud Services - Web Desktop

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A Dedicate Compute Node + No time limt + reserved for certain group/lab

https://portal.biohpc.swmed.edu/terminal/webdesktop/

This service allows certain BioHPC groups to launch long-running interactive

sessions on a dedicated GPU visualization server. There is no time limit for these sessions, but the server is shared among multiple users in the group.

4 Tesla K80 GPU cards

Cloud Services - BioHPC OnDemand

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A Dedicate Compute Node + Service

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DIGITS is a Python-based frontend for machine-learning tools Caffe, Tensorflow, and Torch

Helps reduce the workload of building an artificial neural network

Lots of computing power needed to do the training – uses dual P100 Tesla GPU cards

Cloud Services - BioHPC On-Demand DIGITS

example convolutional neural network

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Radau P, Lu Y, Connelly K, Paul G, Dick AJ, Wright GA. "Evaluation Framework for

Algorithms Segmenting Short Axis Cardiac MRI." The MIDAS Journal -Cardiac MR Left

Ventricle Segmentation Challenge, http://hdl.handle.net/10380/3070

Image segmentation example – Locate left ventricle of the heart within an MRI

Cloud Services - BioHPC On-Demand DIGITS

Tutorial: https://github.com/NVIDIA/DIGITS/blob/master/examples/medical-imaging/README.md

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1. Create a Dataset

Cloud Services - BioHPC On-Demand DIGITS

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2. Create and Train a Model

Cloud Services - BioHPC On-Demand DIGITS

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Cloud Services - BioHPC On-Demand DIGITS

3. Test inference on validation data

Cloud Services - BioHPC On-Demand Jupyter

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What is a Jupyter Notebook?

• Interactive document that contains both computer code and rich text elements

• Python code snippets• Paragraph• Equations• Figures• Links

• What is it for?

• Writing code• Publication-quality figures• Class exercises• Reproducibility• Building webpages

Source: https://plot.ly/python/ipython-notebook-tutorial/

Cloud Services - BioHPC On-Demand Jupyter

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Cloud Services - BioHPC On-Demand Jupyter

Demo: Using Bokeh for Visualizing and Exploring Data in Jupyter

https://github.com/bokeh/bokeh-notebooks/tree/master/quickstart

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* You may also use https://rstudio.biohpc.swmed.edu for small tasks

Use your BioHPC username and password to login

Cloud Services - BioHPC On-Demand RStudio

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Cloud Services - BioHPC On-Demand Bisque (Coming soon)

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Check status of all web-based interactive sessions

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