16 citations · 37 across the 8 of their papers we have counts for
8 papers
TROPHY: Trust Region Optimization Using a Precision Hierarchy
Richard J Clancy, Matt Menickelly, Jan Hückelheim +3
We present an algorithm to perform trust-region-based optimization for nonlinear unconstrained problems. The method selectively uses function and gradient evaluations at different…
Source-to-Source Automatic Differentiation of OpenMP Parallel Loops
Jan Hückelheim, Laurent Hascoët
This paper presents our work toward correct and efficient automatic differentiation of OpenMP parallel worksharing loops in forward and reverse mode. Automatic differentiation is a…
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…
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…
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…