high performance computing on graphics processing units: hgpu.org

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HPC acceleration of large (min, +) matrix products to compute domination-type parameters in graphs

E.M. Garzón, J.A. Martínez, J.J. Moreno, M.L. Puertas

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Tags: Algorithms, Computer science, CUDA, Graph theory, HPC, nVidia, OpenMP, Package, Tesla V100

September 29, 2024 by hgpu

miniLB: A Performance Portability Study of Lattice-Boltzmann Simulations

Luigi Crisci, Biagio Cosenza, Giorgio Amati, Matteo Turisini

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Tags: AMD Radeon Instinct MI100, ATI, cfd, Fluid dynamics, nVidia, Package, SYCL, Tesla V100

September 29, 2024 by hgpu

OpenACC offloading of the MFC compressible multiphase flow solver on AMD and NVIDIA GPUs

Benjamin Wilfong, Anand Radhakrishnan, Henry A. Le Berre, Steve Abbott, Reuben D. Budiardja, Spencer H. Bryngelson

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Tags: AMD Radeon Instinct MI250X, ATI, cfd, Fluid dynamics, MPI, nVidia, OpenACC, Package, Tesla V100

September 29, 2024 by hgpu

Enhancing Code Portability, Problem Scale, and Storage Efficiency in Exascale Applicationsin Exascale Applications

Nigel Tan

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Tags: AMD Radeon Vega VII, ATI, Computer science, CUDA, Heterogeneous systems, HPC, nVidia, nVidia A100, nVidia DGX-A100, nVidia Quadro RTX 5000, OpenMP, OpenMPI, Particle-in-cell methods, performance portability, Tesla V100, Thesis

September 15, 2024 by hgpu

Abstractions for C++ code optimizations in parallel high-performance applications

Jiří Klepl, Adam Šmelko, Lukáš Rozsypal, Martin Kruliš

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Tags: Auto-Tuning, Computer science, CUDA, Data Structures and Algorithms, HPC, nVidia, Package, Tesla V100

August 25, 2024 by hgpu

Evaluating Operators in Deep Neural Networks for Improving Performance Portability of SYCL

Zheming Jin

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Tags: Benchmarking, Computer science, CUDA, HIP, Machine learning, Neural networks, nVidia, nVidia GeForce RTX 2080, nVidia GeForce RTX 3090, nVidia H100, oneAPI, Performance, performance portability, SYCL, Tesla A100, Tesla V100

August 14, 2024 by hgpu

LO-SpMM: Low-cost Search for High-performance SpMM Kernels on GPUs

Junqing Lin, Jingwei Sun, Xiaolong Shi, Honghe Zhang, Xianzhi Yu, Xinzhi Wang, Jun Yao, Guangzhong Sun

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Tags: Compilers, Computer science, CUDA, Deep learning, Linear Algebra, Matrix multiplication, Neural networks, nVidia, nVidia GeForce RTX 2080 Ti, Performance, Sparse matrix, Tesla V100

August 4, 2024 by hgpu

RBMD: A molecular dynamics package enabling to simulate 10 million all-atom particles in a single graphics processing unit

Weihang Gao, Teng Zhao, Yongfa Guo, Jiuyang Liang, Huan Liu, Maoying Luo, Zedong Luo, Wei Qin, Yichao Wang, Qi Zhou, Shi Jin, Zhenli Xu

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Tags: Computational Physics, CUDA, Heterogeneous systems, Molecular dynamics, nVidia, nVidia GeForce RTX 4090, Package, Physics, Tesla A100, Tesla V100

July 28, 2024 by hgpu

Optimization of Large-Scale Sparse Matrix-Vector Multiplication on Multi-GPU Systems

Jianhua Gao, Weixing Ji, Yizhuo Wang

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Tags: Computer science, CUDA, Linear Algebra, nVidia, Optimization, Sparse matrix, Tesla V100

July 14, 2024 by hgpu

Automating Heterogeneous Parallelism in Numerical Differential Equations

Utkarsh

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Tags: AMD RX Vega 64, ATI, Computer science, CUDA, Differential equations, Factorization, Heterogeneous systems, Intel, Intel Arc A770, Julia, Numerical Analysis, nVidia, nVidia Quadro RTX 5000, Package, Tesla V100, Thesis

July 14, 2024 by hgpu

Using Intel oneAPI for Multi-hybrid Acceleration Programming with GPU and FPGA Coupling

Wentao Liang, Norihisa Fujita, Ryohei Kobayashi, Taisuke Boku

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Tags: Computer science, CUDA, FPGA, Heterogeneous systems, nVidia, oneAPI, OpenCL, SYCL, Tesla V100

April 7, 2024 by hgpu

SYCL-Bench 2020: Benchmarking SYCL 2020 on AMD, Intel, and NVIDIA GPUs

Luigi Crisci, Lorenzo Carpentieri, Peter Thoman, Aksel Alpay, Vincent Heuveline, Biagio Cosenza

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Tags: AMD Radeon Instinct MI100, ATI, Benchmarking, Computer science, Heterogeneous systems, HPC, Intel, Intel Ponte Vecchio Max 1100, nVidia, oneAPI, Portability, SYCL, Tesla V100

March 10, 2024 by hgpu

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

Faial: finds bugs in CUDA kernels

Sound and Partially-Complete Static Analysis of Data-Races in GPU Programs

Effects of OpenCL-Based Parallelization Methods on Explicit Numerical Methods to Solve the Heat Equation

Intel® SHMEM: Device initiated shared memory based communication library

Intel(R) SHMEM: GPU-initiated OpenSHMEM using SYCL

miniLB: Lattice Botlzmann miniapp w/SYCL

miniLB: A Performance Portability Study of Lattice-Boltzmann Simulations

AFOCL

Bitstream Database-Driven FPGA Programming Flow Based on Standard OpenCL

2domination

HPC acceleration of large (min, +) matrix products to compute domination-type parameters in graphs

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high performance computing on graphics processing units: hgpu.org

HPC acceleration of large (min, +) matrix products to compute domination-type parameters in graphs

miniLB: A Performance Portability Study of Lattice-Boltzmann Simulations

OpenACC offloading of the MFC compressible multiphase flow solver on AMD and NVIDIA GPUs

Enhancing Code Portability, Problem Scale, and Storage Efficiency in Exascale Applicationsin Exascale Applications

Abstractions for C++ code optimizations in parallel high-performance applications

Evaluating Operators in Deep Neural Networks for Improving Performance Portability of SYCL

LO-SpMM: Low-cost Search for High-performance SpMM Kernels on GPUs

RBMD: A molecular dynamics package enabling to simulate 10 million all-atom particles in a single graphics processing unit

Optimization of Large-Scale Sparse Matrix-Vector Multiplication on Multi-GPU Systems

Automating Heterogeneous Parallelism in Numerical Differential Equations

Using Intel oneAPI for Multi-hybrid Acceleration Programming with GPU and FPGA Coupling

SYCL-Bench 2020: Benchmarking SYCL 2020 on AMD, Intel, and NVIDIA GPUs

Recent source codes

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

EnergyUCB-Bandit

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

Faial: finds bugs in CUDA kernels

Effects of OpenCL-Based Parallelization Methods on Explicit Numerical Methods to Solve the Heat Equation

Intel® SHMEM: Device initiated shared memory based communication library

miniLB: Lattice Botlzmann miniapp w/SYCL

AFOCL

2domination

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