high performance computing on graphics processing units: hgpu.org

Massinissa Merouani, Khaled Afif Boudaoud, Iheb Nassim Aouadj, Nassim Tchoulak, Islam Kara Bernou, Hamza Benyamina, Fatima Benbouzid-Si Tayeb, Karima Benatchba, Hugh Leather, Riyadh Baghdadi

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Tags: Compilers, Computer science, Deep learning, Machine learning, OpenCL, Package, Programming Languages

March 24, 2024 by hgpu

Full-Scale File System Acceleration on GPU

Peter Maucher, Lennard Kittner, Nico Rath, Gregor Lucka, Lukas Werling, Yussuf Khalil, Thorsten Gröninger, Frank Bellosa

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Tags: AMD Radeon RX 6800, ATI, Computer science, Data Structures and Algorithms, HIP, Performance

March 24, 2024 by hgpu

Retargeting and Respecializing GPU Workloads for Performance Portability

Ivan R. Ivanov, Oleksandr Zinenko, Jens Domke, Toshio Endo, William S. Moses

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Tags: AMD Radeon Instinct MI210, AMD Radeon RX 6800, ATI, Computer science, CUDA, HIP, HPC, nVidia, nVidia A100, nVidia RTX A4000, Package, performance portability

March 24, 2024 by hgpu

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

John Tramm, Paul Romano, Patrick Shriwise, Amanda Lund, Johannes Doerfert, Patrick Steinbrecher, Andrew Siegel, Gavin Ridley

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Tags: AMD Radeon Instinct MI250X, ATI, Computer science, CUDA, Intel, Intel Data Center GPU Max 1550, Intel Ponte Vecchio Max 1100, nVidia, nVidia A100, OpenMP, Package, performance portability

March 24, 2024 by hgpu

Parallel Gaussian process with kernel approximation in CUDA

Davide Carminati

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Tags: Benchmarking, Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 1050, nVidia GeForce RTX 2080, Package

March 24, 2024 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

OpenMP offload at the Exascale using Intel GPU Max 1550: evaluation of STREAmS compressible solver

High Performance Privacy Preserving AI

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

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

Speed, power and cost implications for GPU acceleration of Computational Fluid Dynamics on HPC systems

Seer: Predictive Runtime Kernel Selection for Irregular Problems

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

Full-Scale File System Acceleration on GPU

Retargeting and Respecializing GPU Workloads for Performance Portability

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Parallel Gaussian process with kernel approximation in CUDA

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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