The EIT Forward Problem Parallelized Using a Colored pJDS Matrix Format

Abstract

Electrical Impedance Tomography (EIT) is an imaging technique that attempts to reconstruct the conductivity distribution inside an object from electrical currents and potentials applied and measured at its surface. The EIT reconstruction problem is approached as an optimization problem, where the difference between the simulated and measured distributions must be minimized. This work uses the preconditioned conjugated gradients and it has two main modules: matrix-vector multiplication and the triangular solver. The main problem is the solution of a linear system with symmetric positive definite matrix. Several approaches use the compressed sparse row (CSR) format. However, the triangular solver with the CSR format has some thread divergence. In this work, the thread divergence will be eliminated by using the matrix representation called jagged diagonals storage. The proposed GPU accelerated forward solver reduces the expected computational time. Copyright ©2015 IF AC.