Session: Recent Advances on PDE-constrained optimization packages and libraries : Part I
Chair: Noemi Petra
Cluster: Computational Software
Talk 1: Empowering Numerical Optimization Across Disciplines with the Rapid Optimization Library (ROL)
Speaker: Denis Ridzal
Abstract: The Rapid Optimization Library (ROL) is a versatile, high-performance C++ library designed to address the complex demands of numerical optimization in various scientific and engineering disciplines. As an open-source effort through the Trilinos Project, ROL provides an extensive collection of state-of-the-art optimization algorithms capable of handling any application, hardware architecture, and problem size. This talk introduces ROL's key features, including its abstract linear algebra interface for universal applicability, modern algorithms for smooth, constrained, stochastic, risk-aware, and nonsmooth optimization, and its unique PDE-OPT application development kit for PDE-constrained optimization. Additionally, ROL offers an easy-to-use Python interface, which enhances its accessibility and usability across a wider range of applications and user communities. We highlight ROL's successful uses in fields ranging from electrodynamics and fluid dynamics to super-resolution imaging and machine learning. ROL's design philosophy, emphasizing vector abstractions, matrix-free interfaces, and a comprehensive suite of optimization algorithms, positions it as an important tool for researchers seeking to push the boundaries of numerical optimization. Authors: Robert Baraldi, Brian Chen, Aurya Javeed, Drew Kouri, Denis Ridzal, Greg von Winckel, Radoslav Vuchkov
Talk 2: CLAIRE: Constrained Large Deformation Diffeomorphic Image Registration
Speaker: Andreas Mang
Abstract: We present numerical methods for optimal control problems governed by geodesic flows of diffeomorphisms. Our work focuses on designing efficient numerical methods and fast computational kernels for high-performance computing platforms. We aim to compute a flow map that establishes spatial correspondences between two images of the same scene, modeled as geodesic flows of diffeomorphisms. The related optimization problem is non-convex and non-linear, leading to high-dimensional, ill-conditioned systems. Our solvers use advanced algorithms for rapid convergence and employ adjoint-based, second-order methods for numerical optimization. We provide results from real and synthetic data to assess convergence rates, time to solution, accuracy, and scalability of our methods. We also discuss strategies for preconditioning the Hessian and showcase results from our GPU-accelerated software package termed CLAIRE, which is optimized for clinically relevant problems and scales to hundreds of GPUs on modern architectures.
Talk 3: PyOED: An Extensible Suite for Data Assimilation and Model-Constrained Optimal Design of Experiments
Speaker: Ahmed Attia
Abstract: This talk gives a high-level overview of PyOED, a highly extensible scientific package that enables rapid development, testing, and benchmarking of model-based optimal experimental design (OED) methods for inverse problems. PyOED brings together variational and Bayesian data assimilation (DA) algorithms for inverse problems, optimal design of experiments, and novel optimization, statistical, and machine learning methods, into an integrated extensible research environment. PyOED is continuously being expanded with a plethora of Bayesian inference, DA, and OED methods as well as new scientific simulation models, observation error models, priors, and observation operators. These pieces are added such that they can be permuted to enable developing and testing OED methods in various settings of varying complexities. Authors: Ahmed Attia (ANL), Abhijit Chowdhary (NCSU), Shady Ahmed (PNNL)
