Avoiding synchronization to accelerate a CFD solver in GPU

The caffa3d.MBRi is an open source, GPU-aware, general purpose incompressible flow solver, aimed at providing a useful tool for numerical simulation of real world fluid flow problems that require both geometrical flexibility and parallel computation capabilities to afford tens and hundreds million cells simulations. At the core of this tool there are a number of linear solvers that can be selected according to the characteristics of the problem to solve. For band matrices, the most efficient linear solver included in caffa3d.MBRi is the Strongly Implicit Procedure (SIP) solver. The parallelization of this solver follows the hyper-planes strategy, where the computations in one hyper-plane bare no dependencies and can be executed in parallel, while the hyper-planes have to be processed sequentially. In this work, we analyze this strategy to reach an efficient GPU implementation of the SIP solver for the caffa3d.MBRi. In particular, we design and implement a self-scheduling procedure to avoid the overhead of CPU-GPU synchronization implied by the hyper-planes strategy, outperforming the standard GPU implementation of the SIP by approximately 2x.Agencia Nacional de Investigación e Innovació

Placental Flattening via Volumetric Parameterization

We present a volumetric mesh-based algorithm for flattening the placenta to a canonical template to enable effective visualization of local anatomy and function. Monitoring placental function in vivo promises to support pregnancy assessment and to improve care outcomes. We aim to alleviate visualization and interpretation challenges presented by the shape of the placenta when it is attached to the curved uterine wall. To do so, we flatten the volumetric mesh that captures placental shape to resemble the well-studied ex vivo shape. We formulate our method as a map from the in vivo shape to a flattened template that minimizes the symmetric Dirichlet energy to control distortion throughout the volume. Local injectivity is enforced via constrained line search during gradient descent. We evaluate the proposed method on 28 placenta shapes extracted from MRI images in a clinical study of placental function. We achieve sub-voxel accuracy in mapping the boundary of the placenta to the template while successfully controlling distortion throughout the volume. We illustrate how the resulting mapping of the placenta enhances visualization of placental anatomy and function. Our code is freely available at https://github.com/mabulnaga/placenta-flattening .Comment: MICCAI 201