high performance computing on graphics processing units: hgpu.org

Packages

hgpu.org » Applications

GT4Py: High Performance Stencils for Weather and Climate Applications using Python

Enrique G. Paredes, Linus Groner, Stefano Ubbiali, Hannes Vogt, Alberto Madonna, Kean Mariotti, Felipe Cruz, Lucas Benedicic, Mauro Bianco, Joost VandeVondele, Thomas C. Schulthess

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Tags: CUDA, Earth and Space Sciences, nVidia, Package, performance portability, Python, Stencil computation, Tesla P100, Weather prediction

November 27, 2023 by hgpu

Evaluation of FPGA-based high performance computing platforms

Martin Frick-Lundgren

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Tags: Computer science, FPGA, HPC, Intel, Intel UHD 630, Matrix multiplication, OpenCL, Package, SYCL, Thesis

November 27, 2023 by hgpu

Frameworks in Medical Image Analysis with Deep Neural Networks

Dominik Müller

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Tags: Computed tomography, CT, Deep learning, Image processing, Medicine, Microscopy, Neural networks, nVidia, nVidia Titan RTX, Package, Python, Thesis, Tomography

November 27, 2023 by hgpu

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

Bin Lei, Caiwen Ding, Le Chen, Pei-Hung Lin, Chunhua Liao

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Tags: Benchmarking, Computer science, CUDA, Fortran, Machine learning, nVidia, nVidia RTX A6000, OpenMP, Package

November 19, 2023 by hgpu

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

Norihisa Fujita, Beau Johnston, Ryohei Kobayashi, Keita Teranishi, Seyong Lee, Taisuke Boku, Jeffrey S. Vetter

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Tags: AMD Radeon Instinct MI100, ATI, Computer science, CUDA, Heterogeneous systems, nVidia, Package, performance portability, SYCL, Tesla V100

November 19, 2023 by hgpu

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

Topi Leppanen, Joonas Multanen, Leevi Leppänen, Pekka Jääskeläinen

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Tags: Computer science, FPGA, OpenCL, Package, performance portability

November 19, 2023 by hgpu

An approach to performance portability through generic programming

Andreas Hadjigeorgiou, Christodoulos Stylianou, Michele Weiland, Dirk Jacob Verschuur, Jacob Finkenrath

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Tags: AMD Radeon Instinct MI100, ATI, Benchmarking, Computer science, CUDA, HIP, HPC, nVidia, OpenMP, Package, Performance, performance portability, Portability, Tesla V100

November 12, 2023 by hgpu

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

Bowen Tan, Yun Zhu, Lijuan Liu, Hongyi Wang, Yonghao Zhuang, Jindong Chen, Eric Xing, Zhiting Hu

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Tags: Computer science, Deep learning, Distributed computing, nVidia, nVidia A100, Package, TPU

November 5, 2023 by hgpu

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

Shihab Shahriar Khan, Bryce Palmer, Christopher Edelmaierd, Hasan Metin Aktulga

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Tags: Computer science, CUDA, HPC, nVidia, nVidia A100, Package, Pseudo-random number generators, Tesla V100

November 5, 2023 by hgpu

Performance portability evaluation of blocked stencil computations on GPUs

Oscar Antepara, Hans Johansen, Samuel Williams, Tuowen Zhao, Samantha Hirsch, Priya Goyal, Mary Hall

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Tags: AMD Radeon Instinct MI250X, ATI, Code generation, Computer science, CUDA, HIP, nVidia, nVidia A100, Package, performance portability, Stencil computation, SYCL

October 29, 2023 by hgpu

SYCL in the Edge: Performance Evaluation for Heterogeneous Acceleration

Youssef Faqir-Rhazoui, Carlos García

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Tags: Computer science, CUDA, FPGA, Heterogeneous systems, nVidia, nVidia Jetson Nano, Optical flow, Package, SYCL

October 22, 2023 by hgpu

LeXInt: GPU-accelerated Exponential Integrators package

Pranab J. Deka, Alexander Moriggl, Lukas Einkemmer

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Tags: CUDA, Differential equations, Mathematics, nVidia, nVidia A100, Package

October 22, 2023 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

See all packages

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high performance computing on graphics processing units: hgpu.org

Packages

GT4Py: High Performance Stencils for Weather and Climate Applications using Python

Evaluation of FPGA-based high performance computing platforms

Frameworks in Medical Image Analysis with Deep Neural Networks

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

An approach to performance portability through generic programming

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

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

Performance portability evaluation of blocked stencil computations on GPUs

SYCL in the Edge: Performance Evaluation for Heterogeneous Acceleration

LeXInt: GPU-accelerated Exponential Integrators package

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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