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Multi-GPU Jacobian accelerated computing for soft-field tomography.

A Borsic¹, E A Attardo, R J Halter

¹Thayer School of Engineering, Dartmouth College, 8000 Cummings Hall, Hanover, NH 03755, USA. Andrea.Borsic@Dartmouth.edu

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|September 27, 2012

Summary

This summary is machine-generated.

Accelerating 3D image reconstruction in soft-field tomography, like electrical impedance tomography (EIT), is crucial. This study significantly speeds up Jacobian computation using Graphics Processing Units (GPUs), reducing time from minutes to seconds.

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Area of Science:

Medical Imaging
Computational Science
Applied Physics

Background:

Soft-field tomography relies on inverse problem formulation for image reconstruction.
Finite Element Models (FEMs) are used for complex anatomical shapes in 3D modeling.
Current 3D image reconstruction is computationally intensive, with Jacobian matrix computation dominating.

Purpose of the Study:

To accelerate the Jacobian computation for 3D soft-field tomography.
To investigate the use of single and multiple Graphics Processing Units (GPUs) for this acceleration.
To enable faster exploration of data and reconstruction parameters for applications like electrical impedance tomography (EIT).

Main Methods:

Optimized implementation of Jacobian computation on multi-core PC architecture.
Utilized single and multiple GPUs to accelerate Jacobian matrix computation.
Analyzed computational bottlenecks related to CPU-to-memory bandwidth.

Main Results:

Achieved acceleration factors of 20x on a single GPU and 50x on four GPUs.
Reduced Jacobian computation time for a fine 3D mesh from 12 minutes to 14 seconds.
Demonstrated that GPU memory bandwidth and parallelism overcome CPU limitations.

Conclusions:

GPU acceleration significantly reduces computational time for 3D image reconstruction in soft-field tomography.
This advancement is a key step towards achieving interactive reconstruction times.
The method is applicable to various soft-field imaging modalities using the adjoint method for Jacobian computation.