Meeting Users Needs with Octave A survey of the use of Matlab™ and Octave at the NIH Tom Holroyd NIMH MEG Core Facility Presented at the Octave 2006 Workshop April 21, 2006

Outline Survey Results Number of users LicensesUses Other tools Issues for users Octave use at the NIH MEG data analysis Biowulf cluster (2000+ CPUs)

Matlab Users at NIH 25 responses to the survey 9 out of 27 institutes NCI, NHGRI, NLM NHLBI, NIMH, NIAMS NIAID, NIDDK, NIDA

Matlab Users at NIH 35 licenses of various sorts Toolboxes: Statistics 11 Image processing 9 Bioinformatics 6 Signal processing 6 Neural network 4 Optimization 4 Database 3 Curve fitting 3 Spline 1 Symbolic math 1 Fuzzy logic 1 Compiler 1 Excel link 1 Wavelet 1

Many Uses Microarray analysis (6 users) Design Design Visualization Visualization Statistical analysis Statistical analysis Database Database Web site Web site Image processing Content-based image retrieval Content-based image retrieval Segmentation Segmentation Compression Compression Optical and electron microscope image analysis Optical and electron microscope image analysis MRI data analysis Functional mapping Functional mapping Information-based mapping Information-based mapping Voxel-based morphometry Voxel-based morphometry MRI modelling, image reconstruction MRI modelling, image reconstruction Diffusion tensor imaging Diffusion tensor imaging Statistics Statistics General purpose statistics t-tests, ANOVA, regression, etc. t-tests, ANOVA, regression, etc. Neural networks Pattern recognition in mass spectra Pattern recognition in mass spectra Feature extraction Feature extraction

Many, Many Uses Genetics Novel motif discovery in regulatory regions of genomes Novel motif discovery in regulatory regions of genomes Signal processing Mass spectrometry Mass spectrometryInstrumentation Real time control and data acquisition Real time control and data acquisitionNeurophysiology MatOFF: M-series OFFline Analysis for Neurophysiology MatOFF: M-series OFFline Analysis for Neurophysiology MEG data analysis Time-frequency plots Time-frequency plots Multitaper spectral analysis Multitaper spectral analysis Magnetic field simulations Magnetic field simulations Statistics Statistics Realtime BCI Realtime BCI Fieldtrip: ported to Octave Fieldtrip: ported to Octave Curve fitting Fluorescence recovery after photobleaching Fluorescence recovery after photobleaching Simulations of differential equations

Other Tools RScilabmatplotlib/pylab The competition? Data import/export issues exist. RJavaC/C++ Extension packages written in other languages.

Issues for Users Licensing Multi-processor and cluster Platform OS X compatibility 64-bit systems and large memory (> 2GB) Octave Lack of GUI support (not an IDE) Compatibility/portability issues with other analysis packages Speed (we need to convert more.m files to C++) Support, e.g., bioinformatics experts

The License Hog This ran for a week. What the note doesn't say is that he was also using a license; nobody else could use Matlab for a week. I had a user who ran a long job which failed right at the end when it needed to do a t-test and the stats toolbox was busy.

Multiple Processor / Cluster As an example, the Biowulf has 11 licenses (22 CPUs) and various toolboxes costing $96,000. MathWorks can sell us a “cluster” license on 128 CPUs for $39,000. Cheaper, but still about 1900 CPUs short. It works out to about $273 / CPU or $500,000 for the whole cluster (they have never sold a 2000 CPU license).

Octave use at the NIH Magnetoencephalography (MEG) is the recording and analysis of the magnetic field of the brain. NIH has a 275 channel scanner, which produces very large multivariate datasets. Analysis methods include time-frequency plots, magnetic field calculations, and source localization via power spectrum estimation. All can be done with Octave.

Contour Plots The time-frequency graph shown here was calculated using Octave with a C++ extension, then the data were exported to pylab for rendering in a manner similar to that used for Gnuplot. Stockwell Transform

MEG Source Localization Power spectral estimates are used to generate maps of brain activity. We get a timecourse for each voxel. Octave is used as a compute engine here; we run hundreds of such datasets on the cluster. Voxels are all independent!

Biowulf Cluster Recent patches to Octave (not in CVS yet!) make it possible to run in a very large cluster environment. The issue was that Octave's cache of.m files was broken, and it was hitting the NFS server every function call. Now it caches both successes and failures. The new issue is that it won't see new files, although it will pick up files whose modification time has changed. New issues: how to get 200 running Octaves to communicate usefully with each other, for highly parallel computations.

Octave 2006 Workshop Congratulations to all on a successful workshop! See you all at Octave 2007