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On the accuracy and performance of the lattice Boltzmann method with 64-bit, 32-bit and novel 16-bit number formats

Moritz Lehmann, Mathias J. Krause, Giorgio Amati, Marcello Sega, Jens Harting, Stephan Gekle

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Tags: AMD Radeon Instinct MI100, AMD Radeon VI, ATI, Fluid dynamics, lattice Boltzmann, Mixed precision, nVidia, OpenCL, Tesla K20, Tesla K40, Tesla K80, Tesla P100, Tesla V100

December 19, 2021 by hgpu

High performance computing on Android devices – a case study

Robert Fritze, Claudia Plant

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Tags: AMD Radeon VII, Android, ATI, Benchmarking, Computer science, HPC, nVidia GeForce Titan V, OpenCL

December 12, 2021 by hgpu

Generating GPU Compiler Heuristics using Reinforcement Learning

Ian Colbert, Jake Daly, Norm Rubin

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Tags: AMD Radeon 6800 XT, AMD Radeon RX 5700 XT, ATI, Compilers, Computer science, Machine learning, Performance

November 28, 2021 by hgpu

Homomorphic-Encrypted Volume Rendering

Sebastian Mazza

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Tags: Algorithms, AMD Radeon RX 580, ATI, Computer science, GLSL, nVidia, nVidia GeForce RTX 3090, Package, Rendering, Security, Thesis, Visualization, Vulkan

October 17, 2021 by hgpu

Embedded Software Synthesis using Heterogeneous Dataflow Models

Omair Rafique

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Tags: ATI, ATI Radeon HD 5450, Code generation, Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX 1050, nVidia GeForce GTX 950 M, OpenCL, Thesis

October 3, 2021 by hgpu

Achieving near native runtime performance and cross-platform performance portability for random number generation through SYCL interoperability

Vincent R. Pascuzzi, Mehdi Goli

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Tags: AMD Radeon RX Vega 56, ATI, Computer science, Heterogeneous systems, nVidia, nVidia A100, performance portability, Pseudo-random number generators, SYCL

September 19, 2021 by hgpu

Measurement and Analysis of GPU-accelerated Applications with HPCToolkit

Keren Zhou, Laksono Adhianto, Jonathon Anderson, Aaron Cherian, Dejan Grubisic, Mark Krentel, Yumeng Liu, Xiaozhu Meng, John Mellor-Crummey

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Tags: AMD Radeon Instinct Mi50, ATI, Code generation, Computer science, HPC, nVidia, OpenCL, Performance, Tesla V100

September 19, 2021 by hgpu

GPU Algorithms for Efficient Exascale Discretizations

Ahmad Abdelfattah, Valeria Barra, Natalie Beams, Ryan Bleile, Jed Brown, Jean-Sylvain Camier, Robert Carson, Noel Chalmers, Veselin Dobrev, Yohann Dudouit, Paul Fischer, Ali Karakus, Stefan Kerkemeier, Tzanio Kolev, Yu-Hsiang Lan, Elia Merzari, Misun Min, Malachi Phillips, Thilina Rathnayake, Robert Rieben, Thomas Stitt, Ananias Tomboulides, Stanimire Tomov, Vladimir Tomov, Arturo Vargas, Tim Warburton, Kenneth Weiss

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Tags: Algorithms, AMD Radeon Instinct MI100, ATI, Computer science, CUDA, Finite element method, nVidia, OCCA, Tesla V100

September 19, 2021 by hgpu

Raster Time Series: Learning and Processing

Johannes Drönner

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Tags: AMD Radeon RX 580, ATI, Computer science, Deep learning, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan X, OpenCL, Sensing, Thesis, Visualization

May 16, 2021 by hgpu

Efficacy of Images Versus Data Buffers: Optimizing Interactive Applications Utilizing OpenCL for Scientific Visualization

Donald W. Johnson, T. J. Jankun-Kelly

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Tags: AMD Radeon HD 7950, ATI, Computer science, Interactive application, OpenCL, Visualization

May 9, 2021 by hgpu

Daisen: A Framework for Visualizing Detailed GPU Execution

Yifan Sun, Yixuan Zhang, Ali Mosallaei, Michael D. Shah, Cody Dunne, David Kaeli

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Tags: AMD R9 Nano, Artificial intelligence, ATI, Computer science, CUDA, Hardware Architecture, nVidia, OpenCL, Visualization

April 5, 2021 by hgpu

Porting a sparse linear algebra math library to Intel GPUs

Yuhsiang M. Tsai, Terry Cojean, Hartwig Anzt

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Tags: AMD Radeon VII, ATI, Benchmarking, Computer science, HIP, Linear Algebra, nVidia, Package, Performance, Sparse, Sparse matrix, Tesla V100

March 21, 2021 by hgpu

Fancier High-Performance API

Fancier: A Unified Framework for Java, C, and OpenCL Integration

A Compiler Framework for Optimizing Dynamic Parallelism on GPUs

A Compiler Framework for Optimizing Dynamic Parallelism on GPUs

GPOEO: a micro-intrusive GPU online energy optimization framework for iterative applications

Dynamic GPU Energy Optimization for Machine Learning Training Workloads

CFU Playground: Full-Stack Open-Source Framework for Tiny Machine Learning (tinyML) Acceleration on FPGAs

From Loop Fusion to Kernel Fusion: A Domain-specific Approach to Locality Optimization

System-Level Optimization and Code Generation for Graphics Processors using a Domain-Specific Language

Faster-Mean-Shift-Euc

GPU-accelerated Faster Mean Shift with euclidean distance metrics

Turbo: A constraint solver purely on GPUs (CUDA)

A Variant of Concurrent Constraint Programming on GPU

ProGraML: Program Graphs for Machine Learning

PROGRAML: A Graph-based Program Representation for Data Flow Analysis and Compiler Optimizations

Datoviz: GPU interactive scientific data visualization with Vulkan

High-Performance Interactive Scientific Visualization With Datoviz via the Vulkan Low-Level GPU API

NetKet 3: Machine Learning Toolbox for Many-Body Quantum Systems

NetKet 3: Machine Learning Toolbox for Many-Body Quantum Systems

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