high performance computing on graphics processing units: hgpu.org

Hervé Yviquel, Marcio Pereira, Emílio Francesquini, Guilherme Valarini, Gustavo Leite, Pedro Rosso, Rodrigo Ceccato, Carla Cusihualpa, Vitoria Dias, Sandro Rigo, Alan Sousa, Guido Araujo

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Tags: Computer science, MPI, OpenMP, Package

July 17, 2022 by hgpu

CuPBoP: CUDA for Parallelized and Broad-range Processors

Ruobing Han, Jun Chen, Bhanu Garg, Jeffrey Young, Jaewoong Sim, Hyesoon Kim

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Tags: Benchmarking, Compilers, Computer science, CUDA, Heterogeneous systems, HIP, MPI, nVidia, nVidia GeForce GTX 1660 Ti, OpenMP

June 19, 2022 by hgpu

Efficient Execution of OpenMP on GPUs

Joseph Huber, Melanie Cornelius, Giorgis Georgakoudis, Shilei Tian, Jose M Monsalve Diaz, Kuter Dinel, Barbara Chapman, Johannes Doerfert

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Tags: Code generation, Computer science, CUDA, Heterogeneous systems, HPC, LLVM, nVidia, OpenMP, Package, Tesla V100

May 1, 2022 by hgpu

Integrating SkePU’s algorithmic skeletons with GPI on a cluster

Joel Almqvist

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Tags: Computer science, CUDA, Distributed computing, HPC, MPI, nVidia, OpenCL, OpenMP, Thesis

March 6, 2022 by hgpu

Programming Heterogeneous Systems with General and Domain-Specific Frameworks

Lukas Sommer

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Tags: Computer science, CUDA, FPGA, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce RTX 2070, OpenCL, OpenMP, Package, Python, Thesis

November 21, 2021 by hgpu

Creating a Dataset for High-Performance Computing Code Translation using LLMs: A Bridge Between OpenMP Fortran and C+

CHARM-SYCL: New Unified Programming Environment for Multiple Accelerator Types

AFOCL: Portable OpenCL Programming of FPGAs via Automated Built-in Kernel Management

pp-template: Template for Performance-Portable code development, targeting HOST-DEVICE computer architectures

An approach to performance portability through generic programming

Redco: A Lightweight Tool to Automate Distributed Training

Redco: A Lightweight Tool to Automate Distributed Training of LLMs on Any GPU/TPUs

OpenRAND: Reproducible Random Number For Parallel Computations

OpenRAND: A Performance Portable, Reproducible Random Number Generation Library for Parallel Computations

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high performance computing on graphics processing units: hgpu.org

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

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

OpenMP Offloading in the Jetson Nano Platform

MSREP: A Fast yet Light Sparse Matrix Framework for Multi-GPU Systems

Exploiting dynamic sparse matrices for performance portable linear algebra operations

Direct GPU Compilation and Execution for Host Applications with OpenMP Parallelism

Just-in-Time Compilation and Link-Time Optimization for OpenMP Target Offloading

The OpenMP Cluster Programming Model

CuPBoP: CUDA for Parallelized and Broad-range Processors

Efficient Execution of OpenMP on GPUs

Integrating SkePU’s algorithmic skeletons with GPI on a cluster

Programming Heterogeneous Systems with General and Domain-Specific Frameworks

Recent source codes

miniBUDE: A BUDE virtual-screening benchmark, in many programming models

gossip: Efficient Communication Primitives for Multi-GPU Systems

GT4Py: GridTools for Python

AUCMEDI: a framework for Automated Classification of Medical Images

Creating a Dataset for High-Performance Computing Code Translation using LLMs: A Bridge Between OpenMP Fortran and C+

CHARM-SYCL: New Unified Programming Environment for Multiple Accelerator Types

AFOCL: Portable OpenCL Programming of FPGAs via Automated Built-in Kernel Management

pp-template: Template for Performance-Portable code development, targeting HOST-DEVICE computer architectures

Redco: A Lightweight Tool to Automate Distributed Training

OpenRAND: Reproducible Random Number For Parallel Computations

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