Blue Brain Project

Carlos Osuna, Carlos Aguado, Fabien Delalondre

Outline

● Blue Brain Project (BBP) Optimizer Framework: Single neuron simulation

● Implementation Status & models (MPI & BOINC)

● Future directions: Simplifying development workflow (CERN)

Blue Brain Project - Modeling

Biology & MotivationMorphology: a exemplar morphology is used as a template.

Ion channels are added to the compartments of the morphology.

Parameters of the ions channels (such as density per channel type) cannotpossible be measured experimentally.

Modeling & AlgorithmsSingle neuron simulation models neuron electrical response

Optimizer Framework: Genetic algorithm scans parameter to select best fitting candidates to data

Werner Van Geit

Neuron simulation

p1, p2, p3,...

Feature extraction

Fit to data / select best candidates

generation

iterate until best candidates converge

Optimization Workflow Neuron simulation executed using different input protocols (p1, p2, …) to obtain electrical activity of a single neuron

Goodness of model can be evaluated by comparing certain features of electrical response with data.

Werner Van Geit

master

slaves

task submit

Each set of parameters in the phase space, and each protocol is an independent neuron simulation

No communication involve among slaves

p1

p2

p3

Optimizater Task Distribution

master

slaves

task submit

master

slaves

return outcome to master

master

slaves

Evaluate features of

current generation

it best fit can be improved

Genetic Algorithm Flow

MPI/BOINC implementation

Implementation 1: Pure MPI (fast interconnect)

Implementation 2: Adding BOINC support to explore new computing models (S. Wenzel)

Cons: BOINC approach requires porting code on all volunteer platforms (windows, linux, …)

Roadmap Extending Volunteer support using CERN software stack (Virtualization)

Making master/slave framework generic by abstracting implementation details (BOINC/CERN/MPI)

Status & Roadmap