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GDlog: A GPU-Accelerated Deductive Engine

Yihao Sun, Ahmedur Rahman Shovon, Thomas Gilray, Kristopher Micinski, Sidharth Kumar

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Tags: Computer science, CUDA, Databases, nVidia, nVidia A100

November 12, 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

Performance Optimization of Deep Learning Sparse Matrix Kernels on Intel Max Series GPU

Mohammad Zubair, Christoph Bauinger

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Tags: Computer science, CUDA, Deep learning, Intel, Intel Data Center GPU Max 1550, Linear Algebra, Machine learning, Mathematical Software, Matrix multiplication, nVidia, nVidia V100, Sparse matrix, SYCL

November 5, 2023 by hgpu

Applying the Midas Touch of Reproducibility to High-Performance Computing

A. C. Minor, W. Feng

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Tags: Computer science, CUDA, Heterogeneous systems, HPC, nVidia, OpenCL, SYCL

November 5, 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

A Comparison of the Performance of the Molecular Dynamics Simulation Package GROMACS Implemented in the SYCL and CUDA Programming Models

Leonard Apanasevich, Yogesh Kale, Himanshu Sharma, Ana Marija Sokovic

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Tags: Benchmarking, Bioinformatics, Biology, Chemistry, Computer science, CUDA, Heterogeneous systems, Molecular dynamics, nVidia, nVidia A100, nVidia P100, nVidia V100, OpenCL, OpenMP, Performance, SYCL

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 Tuning for GPU-Embedded Systems: Machine-Learning-based and Analytical Model-driven Tuning Methodologies

Adrian Perez Dieguez, Margarita Amor Lopez

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Tags: Computer science, CUDA, FFT, Machine learning, nVidia, nVidia Jetson TX1, Performance, performance portability

October 29, 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

Dynamic autotuning of SpMV kernel in CUSP library

Miroslav Demek

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Tags: Auto-Tuning, Computer science, nVidia, nVidia GeForce GTX 1070, nVidia GeForce RTX 2080, Performance, Sparse matrix, Thesis

October 29, 2023 by hgpu

A Performance-Portable SYCL Implementation of CRK-HACC for Exascale

Esteban M. Rangel, S. John Pennycook, Adrian Pope, Nicholas Frontiere, Zhiqiang Ma, Varsha Madananth

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Tags: AMD Radeon Instinct MI250X, ATI, Computer science, Cosmology, CUDA, HIP, HPC, nVidia, nVidia A100, Performance, performance portability, Physics, SYCL

October 29, 2023 by hgpu

GEVO-ML: Optimizing Machine Learning Code with Evolutionary Computation

Jhe-Yu Liou, Stephanie Forrest, Carole-Jean Wu

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Tags: Computer science, CUDA, Deep learning, Evolutionary Computations, Machine learning, Neural and Evolutionary Computing, nVidia, nVidia P100

October 29, 2023 by hgpu

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

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

Optical flow algorithms for SYCL

SYCL in the edge: performance and energy evaluation for heterogeneous acceleration

OpenMP5-Offload-OpenMC-Intel-PVC

Distributed OpenMP Offloading of OpenMC on Intel GPU MAX Accelerators

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high performance computing on graphics processing units: hgpu.org

Applications

GDlog: A GPU-Accelerated Deductive Engine

An approach to performance portability through generic programming

Performance Optimization of Deep Learning Sparse Matrix Kernels on Intel Max Series GPU

Applying the Midas Touch of Reproducibility to High-Performance Computing

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

A Comparison of the Performance of the Molecular Dynamics Simulation Package GROMACS Implemented in the SYCL and CUDA Programming Models

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

Performance Tuning for GPU-Embedded Systems: Machine-Learning-based and Analytical Model-driven Tuning Methodologies

Performance portability evaluation of blocked stencil computations on GPUs

Dynamic autotuning of SpMV kernel in CUSP library

A Performance-Portable SYCL Implementation of CRK-HACC for Exascale

GEVO-ML: Optimizing Machine Learning Code with Evolutionary Computation

Recent source codes

QArray

Celerity: High-level C++ for Accelerator Clusters

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

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

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

Optical flow algorithms for SYCL

OpenMP5-Offload-OpenMC-Intel-PVC

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