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Multi-GPU thermal lattice Boltzmann simulations using OpenACC and MPI

Ao Xu, Bo-Tao Li

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Tags: cfd, Fluid dynamics, Lattice Boltzmann model, MPI, OpenACC

November 13, 2022 by hgpu

Enabling Data Movement and Computation Pipelining in Deep Learning Compiler

Guyue Huang, Yang Bai, Liu Liu, Yuke Wang, Bei Yu, Yufei Ding, Yuan Xie

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Tags: Computer science, CUDA, Deep learning, nVidia, nVidia A100

November 6, 2022 by hgpu

Using scheduling entropy amplification in CUDA/OpenMP code to exhibit non-reproducibility issues

David Defour

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Tags: Computer science, CUDA, Floating point error, nVidia, nVidia GeForce RTX 2060, OpenMP

November 6, 2022 by hgpu

An Open-source FPGA Library for Data Sorting

Ryohei Kobayashi, Kento Miura, Norihisa Fujita, Taisuke Boku, Toshiyuki Amagasa

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Tags: Algorithms, Computer science, FPGA, OpenCL, Package, Sorting

November 6, 2022 by hgpu

Apple Silicon Performance in Scientific Computing

Connor Kenyon, Collin Capano

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Tags: Benchmarking, Computer science, Heterogeneous systems, nVidia, nVidia A100, nVidia V100, OpenCL, Performance

November 6, 2022 by hgpu

The Open MatSci ML Toolkit: A Flexible Framework for Machine Learning in Materials Science

Santiago Miret, Kin Long Kelvin Lee, Carmelo Gonzales, Marcel Nassar, Matthew Spellings

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Tags: Artificial intelligence, Computer science, Deep learning, Machine learning, Materials Science, Neural networks, Package, Python

November 6, 2022 by hgpu

A systematic performance study of the parallel programming framework SkePU 3 using HPC-benchmarks

Erik Tedhamre

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Tags: Benchmarking, Computer science, CUDA, HPC, nVidia, OpenCL, OpenMP, Package, Performance

October 30, 2022 by hgpu

Benchmarking GPU and TPU Performance with Graph Neural Networks

Xiangyang Ju, Yunsong Wang, Daniel Murnane, Nicholas Choma, Steven Farrell, Paolo Calafiura

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Tags: Artificial intelligence, Benchmarking, Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia A100, Pattern recognition, Tesla V100, TPU

October 30, 2022 by hgpu

gSuite: A Flexible and Framework Independent Benchmark Suite for Graph Neural Network Inference on GPUs

Taha Tekdoğan, Serkan Göktaş, Ayse Yilmazer-Metin

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Tags: Benchmarking, Computer science, CUDA, Machine learning, Neural networks, nVidia, Performance, Tesla V100

October 30, 2022 by hgpu

Providing performance portable numerics for Intel GPUs

Yu-Hsiang M. Tsai, Terry Cojean, Hartwig Anzt

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Tags: AMD Radeon Instinct MI100, ATI, Computer science, CUDA, Linear Algebra, nVidia, nVidia A100, OpenCL, Package, performance portability, Sparse, SYCL

October 30, 2022 by hgpu

torchode: A Parallel ODE Solver for PyTorch

Marten Lienen, Stephan Günnemann

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Tags: Computer science, Deep learning, Numerical Analysis, nVidia, nVidia GeForce GTX 1080 Ti, ODEs, Ordinary differential equations, Package, PyTorch

October 30, 2022 by hgpu

A Ray Tracing Implementation Performance Comparison between the CPU and the GPU

Robin Nordmark, Tim Olsén

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Tags: 3D Graphics and Realism, CUDA, nVidia, nVidia GeForce GTX 1070, Package, Raytracing, Rendering

October 23, 2022 by hgpu

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

SW#SYCL

Analyzing the Performance Portability of SYCL across CPUs, GPUs, and Hybrid Systems with Protein Database Search

tdg-benchs: benchmarks used to test the performance of taskgraph

Leveraging the potential of task-based programming with OpenMP task graphs

LLOR: Automatic Repair of OpenMP Programs

LLOR: Automated Repair of OpenMP Programs

Solomon: Simple Off-LOading Macros Orchestrating multiple Notations

Unified schemes for directive-based GPU offloading

CLUEstering: a high-performance density-based clustering library for scientific computing

PyOMP: OpenMP for Python in Numba

PyOMP: Parallel programming for CPUs and GPUs with OpenMP and Python

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high performance computing on graphics processing units: hgpu.org

Applications

Multi-GPU thermal lattice Boltzmann simulations using OpenACC and MPI

Enabling Data Movement and Computation Pipelining in Deep Learning Compiler

Using scheduling entropy amplification in CUDA/OpenMP code to exhibit non-reproducibility issues

An Open-source FPGA Library for Data Sorting

Apple Silicon Performance in Scientific Computing

The Open MatSci ML Toolkit: A Flexible Framework for Machine Learning in Materials Science

A systematic performance study of the parallel programming framework SkePU 3 using HPC-benchmarks

Benchmarking GPU and TPU Performance with Graph Neural Networks

gSuite: A Flexible and Framework Independent Benchmark Suite for Graph Neural Network Inference on GPUs

Providing performance portable numerics for Intel GPUs

torchode: A Parallel ODE Solver for PyTorch

A Ray Tracing Implementation Performance Comparison between the CPU and the GPU

Recent source codes

Matrix multiplication using Tensor Cores in CUDA

CPP Joules: Energy Measurement tool for CPP/CUDA programs

HPC-Coder-v2

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

SW#SYCL

tdg-benchs: benchmarks used to test the performance of taskgraph

LLOR: Automatic Repair of OpenMP Programs

Solomon: Simple Off-LOading Macros Orchestrating multiple Notations

CLUEstering: a high-performance density-based clustering library for scientific computing

PyOMP: OpenMP for Python in Numba

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