@conference {peters2016SEGprs,
	title = {Parallel reformulation of the sequential adjoint-state method},
	booktitle = {SEG Technical Program Expanded Abstracts},
	year = {2016},
	note = {(SEG, Dallas)},
	month = {10},
	pages = {1411-1415},
	abstract = {This abstract is about reducing the total computation time to solve full-waveform inversion problems. A common problem formulation is a nonlinear least-squares problem where the gradient is computed using the adjoint-state algorithm. This formulation offers parallelism for the computation of gradients for different sources and frequencies. The adjoint-state algorithm itself is sequential however and this is a limiting factor when a lot of compute nodes are available and only a few wavefields need to be computed. This situation occurs when stochastic optimization strategies are used to minimize the objective function. We present a parallel reformulation of the sequential adjoint-state algorithm, which allows the forward- and adjoint wavefields to be computed in parallel. Both algorithms are mathematically equivalent but the parallel version is twice as fast in run time. An important characteristic of the proposed algorithm is that one wavefield needs to be computed per source and one per receiver. These fields can be used to apply the (inverse) Gauss-Newton Hessian to a vector without recomputing wavefields. A 2D example shows that good full-waveform inversion results are obtained, even when a small number of sources and receivers is used.},
	keywords = {FWI, numerical linear algebra, parallel computing, PDE-constrained optimization, SEG},
	doi = {10.1190/segam2016-13966771.1},
	url = {https://slim.gatech.edu/Publications/Public/Conferences/SEG/2016/peters2016SEGprs/peters2016SEGprs.html},
	presentation = {https://slim.gatech.edu/Publications/Public/Conferences/SEG/2016/peters2016SEGprs/peters2016SEGprs_pres.pdf},
	author = {Bas Peters and Tristan van Leeuwen and Felix J. Herrmann}
}
@conference {peters2015SIAMmfq,
	title = {Matrix-free quadratic-penalty methods for PDE-constrained optimization},
	booktitle = {SIAM Conference on Computational Science and Engineering},
	year = {2015},
	note = {(SIAM, Salt Lake City)},
	month = {03},
	abstract = {The large scale of seismic waveform inversion makes matrix free implementations essential. We show how to exploit the quadratic penalty structure to construct matrix free reduced-space and full-space algorithms, which have some advantages over the commonly used Lagrangian based methods for PDE-constrained optimization. This includes the construction of effective and sparse Hessian approximations and reduced sensitivity to the initial guess. A computational bottleneck is the need to solve a large least squares problem with a PDE block. When direct solvers are not available, we propose a fast matrix free iterative approach with reasonable memory requirements. It takes advantage of the structure of the least squares problem with a combination of preconditioning, low rank decomposition and deflation.},
	keywords = {least-squares, low-rank, PDE-constrained optimization, quadratic-penalty, waveform inversion},
	url = {https://slim.gatech.edu/Publications/Public/Conferences/SIAM/2015/peters2015SIAMmfq/peters2015SIAMmfq.pdf},
	author = {Bas Peters and Felix J. Herrmann and Chen Greif}
}
@conference {peters2015SEGWSsew,
	title = {Simultaneous estimation of wavefields and medium parameters - reduced-space versus full-space waveform inversion},
	booktitle = {SEG Workshop on The Limit of FWI in Subsurface Parameter Recovery; New Orleans},
	year = {2015},
	note = {(SEG, New Orleans)},
	month = {10},
	keywords = {full-space, PDE-constrained optimization, quadratic penalty method, SEG, waveform inversion, workshop},
	url = {https://slim.gatech.edu/Publications/Public/Conferences/SEG/2015/peters2015SEGWSsew/peters2015SEGWSsew_pres.pdf},
	author = {Bas Peters and Felix J. Herrmann}
}
