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Gradient compression alleviates expensive communication in distributed deep learning by sending fewer values and its corresponding indices, typically via Allgather (AG). Training with high compression ratio (CR) achieves high accuracy like…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-01-30 Sahil Tyagi , Martin Swany

In this paper we discuss a new and very efficient implementation of high order accurate ADER discontinuous Galerkin (ADER-DG) finite element schemes on modern massively parallel supercomputers. The numerical methods apply to a very broad…

Numerical Analysis · Mathematics 2018-08-20 Michael Dumbser , Francesco Fambri , Maurizio Tavelli , Michael Bader , Tobias Weinzierl

The task of joint dialog sentiment classification (DSC) and act recognition (DAR) aims to simultaneously predict the sentiment label and act label for each utterance in a dialog. In this paper, we put forward a new framework which models…

Computation and Language · Computer Science 2022-03-09 Bowen Xing , Ivor W. Tsang

Algebraic multigrid (AMG) is a widely used scalable solver and preconditioner for large-scale linear systems resulting from the discretization of a wide class of elliptic PDEs. While AMG has optimal computational complexity, the cost of…

Mathematical Software · Computer Science 2020-01-22 Wayne B. Mitchell , Robert Strzodka , Robert D. Falgout

Algebraic multigrid (AMG) is often viewed as a scalable $\mathcal{O}(n)$ solver for sparse linear systems. Yet, parallel AMG lacks scalability due to increasingly large costs associated with communication, both in the initial construction…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-04-25 Amanda Bienz , Luke Olson , William Gropp

The discontinuous Galerkin (DG) method is widely being used to solve hyperbolic partial differential equations (PDEs) due to its ability to provide high-order accurate solutions in complex geometries, capture discontinuities, and exhibit…

Computational Physics · Physics 2024-07-24 Shubham Kumar Goswami , Konduri Aditya

The scalability of time-dependent partial differential equation (PDE) solvers based on the discontinuous Galerkin (DG) method is increasingly limited by data communication and synchronization requirements across processing elements (PEs) at…

Computational Physics · Physics 2026-03-31 Shubham Kumar Goswami , Dapse Vidyesh , Konduri Aditya

In this work, we introduce two novel reformulations of a recent weakly hyperbolic model for two-phase flow with surface tension. In the model, the tracking of phase boundaries is achieved by using a vector interface field, rather than a…

Numerical Analysis · Mathematics 2021-02-03 Simone Chiocchetti , Ilya Peshkov , Sergey Gavrilyuk , Michael Dumbser

Transformer model architectures have become an indispensable staple in deep learning lately for their effectiveness across a range of tasks. Recently, a surge of "X-former" models have been proposed which improve upon the original…

Computation and Language · Computer Science 2021-06-15 Zhe Liu , Yibin Xu

This work presents algorithms for the efficient implementation of discontinuous Galerkin methods with explicit time stepping for acoustic wave propagation on unstructured meshes of quadrilaterals or hexahedra. A crucial step towards…

Numerical Analysis · Computer Science 2019-03-06 Svenja Schoeder , Katharina Kormann , Wolfgang Wall , Martin Kronbichler

Communication remains a key factor limiting the applicability of distributed model predictive control (DMPC) in realistic settings, despite advances in wireless communication. DMPC schemes can require an overwhelming amount of information…

Systems and Control · Electrical Eng. & Systems 2025-11-05 Torben Schiz , Henrik Ebel

The discontinuous Galerkin (DG) method has been widely considered in recent years to develop scalable flow solvers for its ability to handle discontinuities, such as shocks and detonations, with greater accuracy and high arithmetic…

Computational Physics · Physics 2025-01-06 Aswin Kumar Arumugam , Konduri Aditya

Recently, attention-based encoder-decoder (AED) models have shown state-of-the-art performance in automatic speech recognition (ASR). As the original AED models with global attentions are not capable of online inference, various online…

Audio and Speech Processing · Electrical Eng. & Systems 2021-01-15 Hyeonseung Lee , Woo Hyun Kang , Sung Jun Cheon , Hyeongju Kim , Nam Soo Kim

This paper presents an arbitrary h.o. accurate ADER DG method on space-time adaptive meshes (AMR) for the solution of two important families of non-linear time dependent PDE for compr. dissipative flows: the compr. Navier-Stokes equations…

Numerical Analysis · Mathematics 2021-07-22 Francesco Fambri , Michael Dumbser , Olindo Zanotti

We propose a dynamic encoder transducer (DET) for on-device speech recognition. One DET model scales to multiple devices with different computation capacities without retraining or finetuning. To trading off accuracy and latency, DET…

We propose a new paradigm for designing efficient p-adaptive arbitrary high order methods. We consider arbitrary high order iterative schemes that gain one order of accuracy at each iteration and we modify them in order to match the…

Numerical Analysis · Mathematics 2023-11-09 Lorenzo Micalizzi , Davide Torlo , Walter Boscheri

The purpose of this work is to propose a novel a posteriori finite volume subcell limiter technique for the Discontinuous Galerkin finite element method for nonlinear systems of hyperbolic conservation laws in multiple space dimensions that…

Numerical Analysis · Mathematics 2015-03-11 Michael Dumbser , Olindo Zanotti , Raphael Loubere , Steven Diot

In this paper, we propose a unified and high order accurate fully-discrete one-step ADER Discontinuous Galerkin method for the simulation of linear seismic waves in the sea bottom that are generated by the propagation of free surface water…

Numerical Analysis · Mathematics 2020-04-08 Caterina Bassi , Saray Busto , Michael Dumbser

The versatile Arbitrary-DERivative (ADER) scheme is cast in a multilevel framework (ML-ADER) for fast solution of system of linear hyperbolic partial differential equations. The solution is cycled through spatial operators of varying…

Computational Physics · Physics 2017-04-05 S. M. Joshi , A. Chatterjee

Algebraic multigrid (AMG) is an $\mathcal{O}(n)$ solution process for many large sparse linear systems. A hierarchy of progressively coarser grids is constructed that utilize complementary relaxation and interpolation operators. High-energy…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-12-16 Amanda Bienz , Robert D. Falgout William Gropp , Luke N. Olson , Jacob B. Schroder
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