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Experimental Evaluation of Multiprecision Strategies for GMRES on GPUs

Jennifer A. Loe, Christian A. Glusa, Ichitaro Yamazaki, Erik G. Boman, Sivasankaran Rajamanickam

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Tags: Algorithms, CUDA, Linear Algebra, Mathematics, Numerical Analysis, nVidia, performance portability, Tesla V100

May 23, 2021 by hgpu

Solving Mixed Integer Programs Using Neural Networks

Vinod Nair, Sergey Bartunov, Felix Gimeno, Ingrid von Glehn, Pawel Lichocki, Ivan Lobov, Brendan O'Donoghue, Nicolas Sonnerat, Christian Tjandraatmadja, Pengming Wang, Ravichandra Addanki, Tharindi Hapuarachchi, Thomas Keck, James Keeling, Pushmeet Kohli, Ira Ktena, Yujia Li, Oriol Vinyals, Yori Zwols

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Tags: Computer science, Deep learning, Machine learning, Mathematics, Neural networks, nVidia

December 27, 2020 by hgpu

Optimization of a discontinuous Galerkin solver with OpenCL and StarPU

Bérenger Bramas, Philippe Helluy, Laura Mendoza, Bruno Weber

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Tags: Algorithms, Mathematics, nVidia, nVidia GeForce GTX 1050, OpenCL, Package, PDEs, Tesla P100

February 2, 2020 by hgpu

Non-Hydrostatic Pressure Shallow Flows: GPU Implementation Using Finite-Volume and Finite-Difference Scheme

C. Escalante, T. Morales de Luna, M.J. Castro

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Tags: Algorithms, CUDA, Finite difference, Fluid dynamics, Mathematics, Numerical Analysis, nVidia

June 17, 2017 by hgpu

Speeding up a few orders of magnitude the Jacobi method: high order Chebyshev-Jacobi over GPUs

J.E. Adsuara, I. Cordero-Carrion, P. Cerda-Duran, M.A. Aloy

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Tags: CUDA, Differential equations, Finite difference, Mathematics, Numerical Analysis, nVidia, nVidia GeForce GTX Titan X, Partial differential equations, PDEs, Tesla K40

May 2, 2017 by hgpu

Streaming GPU Singular Value and Dynamic Mode Decompositions

Seth D. Pendergrass, J. Nathan Kutz, Steven L. Brunton

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Tags: Algorithms, Computer vision, CUDA, Mathematics, Matrix multiplication, Numerical Analysis, nVidia, Sparse matrix, Tesla K40

December 26, 2016 by hgpu

Feynman Machine: The Universal Dynamical Systems Computer

Eric Laukien, Richard Crowder, Fergal Byrne

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Tags: AMD Radeon R9 290, Artificial intelligence, ATI, Computer science, Deep learning, Mathematics, Neuroscience, OpenCL

September 20, 2016 by hgpu

An efficient numerical method for solving the Boltzmann equation in multidimensions

Giacomo Dimarco, Raphael Loubere, Jacek Narski, Thomas Rey

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Tags: Algorithms, Boltzmann equation, cfd, CUDA, Fluid dynamics, Mathematics, MPI, Numerical Analysis, nVidia, OpenMP, Physics

September 13, 2016 by hgpu

A New Architecture for Optimization Modeling Frameworks

Matt Wytock, Steven Diamond, Felix Heide, Stephen Boyd

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Tags: Algorithms, CUDA, Deep learning, Linear Algebra, Mathematics, nVidia, nVidia GeForce GTX Titan X, Package, Python

September 13, 2016 by hgpu

Fast hyperbolic Radon transform represented as convolutions in log-polar coordinates

Viktor V. Nikitin, Fredrik Andersson, Marcus Carlsson, Anton A. Duchkov

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Tags: CUDA, FFT, Geoscience, Mathematics, Numerical Analysis, nVidia, Radon transform, Seismic modeling

May 3, 2016 by hgpu

GPU-accelerated stochastic predictive control of drinking water networks

Ajay K. Sampathirao, Pantelis Sopasakis, Alberto Bemporad, Panagiotis Patrinos

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Tags: CUDA, Mathematics, nVidia, Tesla C2075

April 6, 2016 by hgpu

GPU-accelerated Bernstein-Bezier discontinuous Galerkin methods for wave problems

Jesse Chan, T. Warburton

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Tags: Mathematics, Numerical Analysis, nVidia, nVidia GeForce GTX 980, OCCA

December 22, 2015 by hgpu

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Clava: C/C++ Source-to-Source Tool based on Clang

Challenges and Opportunities in C/C++ Source-To-Source Compilation

gpuLik

Statistical Computing With Graphics Processing Units

Octo-Tiger: Astrophysics program simulating the evolution of star systems based on the fast multipole method on adaptive Octrees

Stellar Mergers with HPX-Kokkos and SYCL: Methods of using an Asynchronous Many-Task Runtime System with SYCL

BAT: A standardized benchmark suite for auto-tuners

Towards a Benchmarking Suite for Kernel Tuners

BenchDirect: A Directed Language Model for Compiler Benchmarks

BenchDirect: A Directed Language Model for Compiler Benchmarks

A Deep Learning Model for Loop Interchange

A Deep Learning Model for Loop Interchange

Bridging Control-Centric and Data-Centric Optimization

Bridging Control-Centric and Data-Centric Optimization

Advanced evolutionary computation library built directly on top of PyTorch, created at NNAISENSE

EvoTorch: Scalable Evolutionary Computation in Python

DeepAxe: A Framework for Exploration of Approximation and Reliability Trade-offs in DNN Accelerators

DeepAxe: A Framework for Exploration of Approximation and Reliability Trade-offs in DNN Accelerators

RTIndeX: Exploiting Hardware-Accelerated GPU Raytracing for Database Indexing

RTIndeX: Exploiting Hardware-Accelerated GPU Raytracing for Database Indexing

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