GPGPU Accelerated Cardiac Arrhythmia Simulations

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GPGPU Accelerated Cardiac Arrhythmia Simulations

• Wei Wang1, H. Howie Huang2, Matthew Kay2 and John
  Cavazos1
• University of Delaware
• The George Washington University

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Motivation

• Cardiac arrhythmia
• 300,000 people/year in the US
• Cure
• Image-guided ablation therapy
• Simulation improves efficacy
• Problem
• Sequential execution of simulation too slow!

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Simulation Cardiac Model
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Acceleration Concept

• Sequential (Running on CPU)

• Parallel (Enabled by GPGPUs)

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Acceleration ToolGPU

• Example NVIDIA Tesla C1060
• 240 Processing Elements
• Massively parallel multithreaded
• Up to 30720 active threads

CPU
GPU
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Acceleration Considerations

• SIMD
• Large Matrix
• No (Few) Temporal Data Dependency
• Acceleration CommandCUDA
• Using Atomic Functions

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GPU Acceleration
for (Xstep1XstepltNx1Xstep) for
(Ystep1YstepltNy1Ystep)
stimulate() //apply stimulating current
brgates() // update gating equations
brcurrents() // update currents
mdiff() // update diffusion
terms // end Ystep loop // end Xstep loop
bcs() // apply boundary
conditions
GPU_ GPU_ GPU_ GPU_
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Simulation Results

• Point Stimulation

• Electrical Rotor Simulation

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Point Simulation Results
Speedup (normalized to seq perf)
Matrix Sizes
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Thank you!
Wei Wang weiwang_at_udel.edu http//www.cis.udel.edu/
wwang
Please consider GPGPU