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GPGPU Accelerated Cardiac Arrhythmia Simulations
Wei Wang1, H. Howie Huang2, Matthew Kay2 and John Cavazos1
1.University of Delaware2.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)
N11 N21 N31
N12 N22 N32
N13 N23 N33
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Acceleration Tool—GPU• 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 Command—CUDA• Using Atomic Functions*
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GPU Acceleration
for (Xstep=1;Xstep<Nx+1;++Xstep){ for (Ystep=1;Ystep<Ny+1;++Ystep){ 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
Matrix Sizes
S
peed
up
(nor
mal
ized
to
seq
perf
)