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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

On the Performance Portability of Structured Grid Codes on Many-Core Computer Architectures

Simon McIntosh-Smith, Michael Boulton, Dan Curran, James Price

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Tags: CloverLeaf, Fluid dynamics, GPU, Intel Xeon Phi, lattice Boltzmann, OpenCL, performance portability, ROTORSIM, structured grid

June 17, 2014 by simonmcs

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SYCL-DNN: a library implementing neural network algorithms written using SYCL

User-Driven Online Kernel Fusion for SYCL

SW#SYCL

Assessing Opportunities of SYCL and Intel oneAPI for Biological Sequence Alignment

StateMover: a checkpoint-based debugging framework for FPGAs

Hardware Checkpointing and Productive Debugging Flows for FPGAs

Flink-TornadoVM-Artifact

Challenges and Techniques for Transparent Acceleration of Unmodified Big Data Applications

Kernel Tuner

Going green: optimizing GPUs for energy efficiency through model-steered auto-tuning

TorchOpt: an efficient library for differentiable optimization built upon PyTorch

TorchOpt: An Efficient Library for Differentiable Optimization

NaturalCC: An Open-Source Toolkit for Code Intelligence

A Study on Neural-based Code Summarization in Low-resource Settings

mt4g: Memory Topology for GPUs

Capturing the Memory Topology of GPUs

iGniter: an interference-aware GPU resource provisioning framework for achieving predictable performance of DNN inference in the cloud

iGniter: Interference-Aware GPU Resource Provisioning for Predictable DNN Inference in the Cloud

pyGSL: A Scalable Library for Graph Structure Learning

pyGSL: A Graph Structure Learning Toolkit

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