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20152023
most citedAutomatic Differentiation for Adjoint Stencil Loops

12 citations · 31 across the 7 of their papers we have counts for

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8 papers · 1 filter

cs.DC2020

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…

cs.DC2019

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…

cs.DC201912 cited

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…

cs.DC20191 cited

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…

cs.DC2018

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…

cs.DC20157 cited

Thread Parallelism for Highly Irregular Computation in Anisotropic Mesh Adaptation

Georgios Rokos, Gerard J. Gorman, Kristian Ejlebjerg Jensen +1

Thread-level parallelism in irregular applications with mutable data dependencies presents challenges because the underlying data is extensively modified during execution of the al…