202 citations · 431 across the 32 of their papers we have counts for
33 papers
Learned multiphysics inversion with differentiable programming and machine learning
Mathias Louboutin, Ziyi Yin, Rafael Orozco +7
We present the Seismic Laboratory for Imaging and Modeling/Monitoring (SLIM) open-source software framework for computational geophysics and, more generally, inverse problems invol…
PyBryt: auto-assessment and auto-grading for computational thinking
Christopher Pyles, Francois van Schalkwyk, Gerard J. Gorman +4
We continuously interact with computerized systems to achieve goals and perform tasks in our personal and professional lives. Therefore, the ability to program such systems is a sk…
Stride: a flexible platform for high-performance ultrasound computed tomography
Carlos Cueto, Oscar Bates, George Strong +6
Advanced ultrasound computed tomography techniques like full-waveform inversion are mathematically challenging and orders of magnitude more computationally expensive than conventio…
Temporal blocking of finite-difference stencil operators with sparse "off-the-grid" sources
George Bisbas, Fabio Luporini, Mathias Louboutin +3
Stencil kernels dominate a range of scientific applications, including seismic and medical imaging, image processing, and neural networks. Temporal blocking is a performance optimi…
Lossy Checkpoint Compression in Full Waveform Inversion: a case study with ZFPv0.5.5 and the Overthrust Model
Navjot Kukreja, Jan Hueckelheim, Mathias Louboutin +3
This paper proposes a new method that combines check-pointing methods with error-controlled lossy compression for large-scale high-performance Full-Waveform Inversion (FWI), an inv…
Scaling through abstractions -- high-performance vectorial wave simulations for seismic inversion with Devito
Mathias Louboutin, Fabio Luporini, Philipp Witte +5
[Devito] is an open-source Python project based on domain-specific language and compiler technology. Driven by the requirements of rapid HPC applications development in exploration…
GPU Support for Automatic Generation of Finite-Differences Stencil Kernels
Vitor Hugo Mickus Rodrigues, Lucas Cavalcante, Maelso Bruno Pereira +4
The growth of data to be processed in the Oil & Gas industry matches the requirements imposed by evolving algorithms based on stencil computations, such as Full Waveform Inversion…
Performance of Devito on HPC-Optimised ARM Processors
Hermes Senger, Jaime F. de Souza, Edson S. Gomi +2
We evaluate the performance of Devito, a domain specific language (DSL) for finite differences on Arm ThunderX2 processors. Experiments with two common seismic computational kernel…
Automatic Differentiation for Adjoint Stencil Loops
Jan Hückelheim, Navjot Kukreja, Sri Hari Krishna Narayanan +3
Stencil loops are a common motif in computations including convolutional neural networks, structured-mesh solvers for partial differential equations, and image processing. Stencil…
Training on the Edge: The why and the how
Navjot Kukreja, Alena Shilova, Olivier Beaumont +4
Edge computing is the natural progression from Cloud computing, where, instead of collecting all data and processing it centrally, like in a cloud computing environment, we distrib…
Combining Checkpointing and Data Compression to Accelerate Adjoint-Based Optimization Problems
Navjot Kukreja, Jan Hueckelheim, Mathias Louboutin +3
Seismic inversion and imaging are adjoint-based optimization problems that process up to terabytes of data, regularly exceeding the memory capacity of available computers. Data com…
Devito (v3.1.0): an embedded domain-specific language for finite differences and geophysical exploration
Mathias Louboutin, Michael Lange, Fabio Luporini +5
We introduce Devito, a new domain-specific language for implementing high-performance finite difference partial differential equation solvers. The motivating application is explora…
Architecture and performance of Devito, a system for automated stencil computation
Fabio Luporini, Michael Lange, Mathias Louboutin +7
Stencil computations are a key part of many high-performance computing applications, such as image processing, convolutional neural networks, and finite-difference solvers for part…
Backpropagation for long sequences: beyond memory constraints with constant overheads
Navjot Kukreja, Jan Hückelheim, Gerard J. Gorman
Naive backpropagation through time has a memory footprint that grows linearly in the sequence length, due to the need to store each state of the forward propagation. This is a prob…
High-level python abstractions for optimal checkpointing in inversion problems
Navjot Kukreja, Jan Hückelheim, Michael Lange +4
Inversion and PDE-constrained optimization problems often rely on solving the adjoint problem to calculate the gradient of the objec- tive function. This requires storing large amo…
Automated Tiling of Unstructured Mesh Computations with Application to Seismological Modelling
Fabio Luporini, Michael Lange, Christian T. Jacobs +3
Sparse tiling is a technique to fuse loops that access common data, thus increasing data locality. Unlike traditional loop fusion or blocking, the loops may have different iteratio…
Optimised finite difference computation from symbolic equations
Michael Lange, Navjot Kukreja, Fabio Luporini +4
Domain-specific high-productivity environments are playing an increasingly important role in scientific computing due to the levels of abstraction and automation they provide. In t…
Anisotropic mesh adaptation in Firedrake with PETSc DMPlex
Nicolas Barral, Matthew G. Knepley, Michael Lange +2
Despite decades of research in this area, mesh adaptation capabilities are still rarely found in numerical simulation software. We postulate that the primary reason for this is lac…
Devito: Towards a generic Finite Difference DSL using Symbolic Python
Michael Lange, Navjot Kukreja, Mathias Louboutin +6
Domain specific languages (DSL) have been used in a variety of fields to express complex scientific problems in a concise manner and provide automated performance optimization for…
Devito: automated fast finite difference computation
Navjot Kukreja, Mathias Louboutin, Felippe Vieira +3
Domain specific languages have successfully been used in a variety of fields to cleanly express scientific problems as well as to simplify implementation and performance opti- miza…
Performance prediction of finite-difference solvers for different computer architectures
Mathias Louboutin, Michael Lange, Felix Herrmann +2
The life-cycle of a partial differential equation (PDE) solver is often characterized by three development phases: the development of a stable numerical discretization, development…
Shoreline and Bathymetry Approximation in Mesh Generation for Tidal Renewable Simulations
Alexandros Avdis, Christian T. Jacobs, Jon Hill +2
Due to the fractal nature of the domain geometry in geophysical flow simulations, a completely accurate description of the domain in terms of a computational mesh is frequently dee…
Efficient mesh management in Firedrake using PETSc-DMPlex
Michael Lange, Lawrence Mitchell, Matthew G. Knepley +1
The use of composable abstractions allows the application of new and established algorithms to a wide range of problems while automatically inheriting the benefits of well-known pe…
Unstructured Overlapping Mesh Distribution in Parallel
Matthew G. Knepley, Michael Lange, Gerard J. Gorman
We present a simple mathematical framework and API for parallel mesh and data distribution, load balancing, and overlap generation. It relies on viewing the mesh as a Hasse diagram…