high performance computing on graphics processing units: hgpu.org

Claudio Bonati, Enrico Calore, Simone Coscetti, Massimo D'Elia, Michele Mesiti, Francesco Negro, Sebastiano Fabio Schifano, Giorgio Silvi, Raffaele Tripiccione

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Tags: AMD FirePro W9100, ATI, Computational Physics, Heterogeneous systems, High Energy Physics - Lattice, nVidia, OpenACC, performance portability, Physics, QCD, Tesla K80, Tesla P100

January 4, 2017 by hgpu

Hierarchical Product Quantization for Approximate Nearest Neighbors Search

Accelerated Approximate Nearest Neighbors Search Through Hierarchical Product Quantization

hlslib: A collection of extensions for Vivado HLS and Intel FPGA OpenCL to improve developer quality of life

hlslib: Software Engineering for Hardware Design

Taichi: A Language for High-Performance Computation on Spatially Sparse Data Structures

MCL kernel verification library

Verification of GPU Program Optimizations in Lean

waLBerla: A block-structured high-performance framework for multiphysics simulations

MIOpen: AMD's Machine Intelligence Library

MIOpen: An Open Source Library For Deep Learning Primitives

horovod: Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet

Exascale Deep Learning for Scientific Inverse Problems

Futhark Vulkan Backend

Megatron-LM: Ongoing research training transformer language models at scale, including: BERT & GPT-2

Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism

Espresso: A Fast End-to-End Neural Speech Recognition Toolkit

Espresso: A Fast End-to-end Neural Speech Recognition Toolkit

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Boston, USA

7th International Workshop on OpenCL, 2019

2019

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Boston, MA, USA

Distributed Heterogeneous Programming in C/C++ (DHPCC++), 2019

2019

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Larnaca, Cyprus

3rd International Workshop on Theoretical Approaches to Performance Evaluation, Modeling and Simulation (TAPEMS), 2019

2019

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26-28

Rome, Italy

International Conference on Frontiers of Neural Networks (ICFNN), 2019

2019

July

26-28

Rome, Italy

International Conference on Frontiers of Artificial Intelligence and Machine Learning (FAIML), 2019

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high performance computing on graphics processing units: hgpu.org

Classify QCD phase transition with deep learning

Towards Lattice Quantum Chromodynamics on FPGA devices

AVX-512 extension to OpenQCD 1.6

Practical Implementation of Lattice QCD Simulation on Intel Xeon Phi Knights Landing

MILC Code Performance on High End CPU and GPU Supercomputer Clusters

Lattice QCD on new chips: a community summary

Wilson and Domainwall Kernels on Oakforest-PACS

Mixed Precision Solver Scalable to 16000 MPI Processes for Lattice Quantum Chromodynamics Simulations on the Oakforest-PACS System

Optimization of the Brillouin operator on the KNL architecture

Lattice Quantum Chromodynamics on Intel Xeon Phi based supercomputers

Machines and Algorithms

Design and optimization of a portable LQCD Monte Carlo code using OpenACC

Recent source codes

Hierarchical Product Quantization for Approximate Nearest Neighbors Search

hlslib: A collection of extensions for Vivado HLS and Intel FPGA OpenCL to improve developer quality of life

Taichi: A Language for High-Performance Computation on Spatially Sparse Data Structures

MCL kernel verification library

waLBerla: A block-structured high-performance framework for multiphysics simulations

MIOpen: AMD's Machine Intelligence Library

horovod: Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet

Futhark Vulkan Backend

Megatron-LM: Ongoing research training transformer language models at scale, including: BERT & GPT-2

Espresso: A Fast End-to-End Neural Speech Recognition Toolkit

Most viewed papers (last 30 days)

Featured events

7th International Workshop on OpenCL, 2019

Distributed Heterogeneous Programming in C/C++ (DHPCC++), 2019

3rd International Workshop on Theoretical Approaches to Performance Evaluation, Modeling and Simulation (TAPEMS), 2019

International Conference on Frontiers of Neural Networks (ICFNN), 2019

International Conference on Frontiers of Artificial Intelligence and Machine Learning (FAIML), 2019