high performance computing on graphics processing units: hgpu.org

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Adaptive Data Migration in Load-Imbalanced HPC Applications

Parsa Amini

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Tags: Computer science, CUDA, Heterogeneous systems, HPC, load balancing, nVidia, Package, Tesla P100, Tesla V100, Thesis

November 15, 2020 by hgpu

Exploring the acceleration of Nekbone on reconfigurable architectures

Nick Brown

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Tags: Computer science, FPGA, HLS, nVidia, OpenCL, Tesla V100

November 15, 2020 by hgpu

Tinker-HP: Accelerating Molecular Dynamics Simulations of Large Complex Systems with Advanced Point Dipole Polarizable Force Fields using GPUs and Multi-GPUs systems

Olivier Adjoua, Louis Lagardère, Luc-Henri Jolly, Arnaud Durocher, Thibaut Very, Isabelle Dupays, Zhi Wang, Théo Jaffrelot Inizan, Frédéric Célerse, Pengyu Ren, Jay W. Ponder, Jean-Philip Piquemal

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Tags: Biophysics, Computational Physics, CUDA, Molecular dynamics, nVidia, nVidia DGX-A100, OpenACC, Package, Physics, Tesla V100

November 8, 2020 by hgpu

Out-of-core Training for Extremely Large-Scale Neural Networks With Adaptive Window-Based Scheduling

Akio Hayakawa, Takuya Narihira

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Tags: Algorithms, Computer science, CUDA, Deep learning, Neural networks, nVidia, Package, Tesla V100

November 1, 2020 by hgpu

Not Half Bad: Exploring Half-Precision in Graph Convolutional Neural Networks

John Brennan, Stephen Bonner, Amir Atapour-Abarghouei, Philip T Jackson, Boguslaw Obara, Andrew Stephen McGough

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Tags: CNN, Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia Titan RTX, PyTorch, Tesla P100, Tesla V100

November 1, 2020 by hgpu

Performance Assessment of OpenMP Compilers Targeting NVIDIA V100 GPUs

Joshua Hoke Davis, Christopher Daley, Swaroop Pophale, Thomas Huber, Sunita Chandrasekaran, Nicholas J. Wright

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenACC, OpenMP, Performance, Tesla V100

October 25, 2020 by hgpu

Mixed-Precision Embedding Using a Cache

Jie (Amy)Yang, Jianyu Huang, Jongsoo Park, Ping Tak Peter Tang, Andrew Tulloch

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Tags: Artificial intelligence, Computer science, CUDA, Machine learning, Mixed precision, nVidia, Tesla V100

October 25, 2020 by hgpu

FlowPM: Distributed TensorFlow Implementation of the FastPM Cosmological N-body Solver

Chirag Modi, Francois Lanusse, Uros Seljak

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Tags: Astrophysics, Cosmology, CUDA, N-body simulation, nVidia, Package, Physics, TensorFlow, Tesla V100

October 25, 2020 by hgpu

Portable high-order finite element kernels I: Streaming Operations

Noel Chalmers, Tim Warburton

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Tags: AMD, AMD Radeon Instinct MI60, AMD Radeon VII, Computer science, CUDA, FEM, HIP, Mathematical Software, nVidia, nVidia GeForce GTX Titan V, OCCA, Portability, Tesla V100

October 18, 2020 by hgpu

Mastering Atari with Discrete World Models

Danijar Hafner, Timothy Lillicrap, Mohammad Norouzi, Jimmy Ba

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Tags: Artificial intelligence, Computer science, Deep learning, Machine learning, nVidia, Package, Python, TensorFlow, Tesla V100

October 11, 2020 by hgpu

Efficient Inference For Neural Machine Translation

Yi-Te Hsu, Sarthak Garg, Yi-Hsiu Liao, Ilya Chatsviorkin

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Tags: Computer science, NLP, nVidia, Tesla V100

October 11, 2020 by hgpu

Hybrid MPI and CUDA Parallelization for CFD Applications on Multi-GPU HPC Clusters

Jianqi Lai, Hang Yu, Zhengyu Tian, Hua Li

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Tags: cfd, CUDA, Fluid dynamics, GPU cluster, HPC, MPI, nVidia, nVidia GeForce GTX 1070, OpenMP, Tesla V100

September 27, 2020 by hgpu

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

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high performance computing on graphics processing units: hgpu.org

Adaptive Data Migration in Load-Imbalanced HPC Applications

Exploring the acceleration of Nekbone on reconfigurable architectures

Tinker-HP: Accelerating Molecular Dynamics Simulations of Large Complex Systems with Advanced Point Dipole Polarizable Force Fields using GPUs and Multi-GPUs systems

Out-of-core Training for Extremely Large-Scale Neural Networks With Adaptive Window-Based Scheduling

Not Half Bad: Exploring Half-Precision in Graph Convolutional Neural Networks

Performance Assessment of OpenMP Compilers Targeting NVIDIA V100 GPUs

Mixed-Precision Embedding Using a Cache

FlowPM: Distributed TensorFlow Implementation of the FastPM Cosmological N-body Solver

Portable high-order finite element kernels I: Streaming Operations

Mastering Atari with Discrete World Models

Efficient Inference For Neural Machine Translation

Hybrid MPI and CUDA Parallelization for CFD Applications on Multi-GPU HPC Clusters

Recent source codes

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

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