high performance computing on graphics processing units: hgpu.org

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The Comparisons of OpenCL and OpenMP Computing Paradigm

Slo-Li Chu, Chih-Chieh Hsiao

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Tags: ATI, ATI Radeon HD 5850, Benchmarking, Computer science, nVidia GeForce GTX 285, OpenCL, OpenMP, Performance

December 9, 2013 by hgpu

A Quantitative Comparison of Emulated Shared Memory Architectures to Current Multicore CPUs and GPUs

Erik Hansson, Erik Alnervik, Christoph Kessler, Martti Forsell

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Tags: Computer science, CUDA, nVidia, Performance, Tesla M2050

December 6, 2013 by hgpu

Applications of Many-Core Technologies to On-line Event Reconstruction in High Energy Physics Experiments

A. Gianelle, S. Amerio, D. Bastieri, M. Corvo, W. Ketchum, T. Liu, A. Lonardo, D. Lucchesi, S. Poprocki, R. Rivera, L. Tosoratto, P. Vicini, P. Wittich

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Tags: ATI, ATI Radeon HD 7970, CUDA, High Energy Physics - Experiment, Instrumentation and Detectors, Intel Xeon Phi, nVidia, nVidia GeForce GTX Titan, OpenCL, Performance, Physics, Tesla K20, Tesla M2050

December 6, 2013 by hgpu

Comparative Study of High Performance Computing Using Multi-core Parallel Systems

Hyo Jong Lee, Hyeon Kyu Kim

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 550 Ti, nVidia GeForce GTX 580, Performance

December 4, 2013 by hgpu

Divergence Analysis

Diogo Sampaio, Rafael Martins De Souza, Sylvain Collange, Fernando Magno Quintao Pereira

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 570, Performance

December 4, 2013 by hgpu

SESH framework: A Space Exploration Framework for GPU Application and Hardware Codesign

Joo Hwan Lee, Jiayuan Meng, Hyesoon Kim

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Tags: Benchmarking, Computer science, nVidia, nVidia GeForce GTX 580, Performance

December 3, 2013 by hgpu

Benchmarking Parallel Performance on Many-Core Processors

Bryant C. Lam, Ajay Barboza, Ravi Agrawal, Alan D. George, Herman Lam

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Tags: Benchmarking, Computer science, Heterogeneous systems, Intel Phi, Intel Xeon Phi, Performance

November 29, 2013 by hgpu

The Future of Accelerator Programming: Abstraction, Performance or Can We Have Both?

Kamil Rocki, Martin Burtscher, Reiji Suda

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Tags: ATI, ATI Radeon HD 7970, Computer science, Intel Phi, Intel Xeon Phi, nVidia, nVidia GeForce GTX Titan, OpenCL, Performance, Programming techniques

November 28, 2013 by hgpu

Hybrid Programming using OpenSHMEM and OpenACC

Matthew Baker, Swaroop Pophale, Jean-Charles Vasnier, Haoqiang Jin, Oscar Hernandez

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Tags: Computer science, CUDA, MPI, nVidia, OpenACC, Performance, Tesla K20

November 28, 2013 by hgpu

Evaluating the Performance and Energy Efficiency of N-Body Codes on Multi-Core CPUs and GPUs

Ivan Zecena, Martin Burtscher, Tongdan Jin, Ziliang Zong

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Tags: Computer science, CUDA, N-body simulation, nVidia, nVidia GeForce GTX 480, Performance

November 27, 2013 by hgpu

Exploring Graphics Processing Unit (GPU) Resource Sharing Efficiency for High Performance Computing

Teng Li, Vikram K. Narayana, Tarek El-Ghazawi

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Tags: Computer science, CUDA, nVidia, Performance, Tesla C2070

November 24, 2013 by hgpu

Dynamic Partitioning-based JPEG Decompression on Heterogeneous Multicore Architectures

Wasuwee Sodsong, Jingun Hong, Seongwook Chung, Shin-Dug Kim, Bernd Burgstaller

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Tags: Compression, Heterogeneous systems, Image processing, nVidia, nVidia GeForce GT 430, nVidia GeForce GTX 560 Ti, nVidia GeForce GTX 680, OpenCL, Performance

November 23, 2013 by hgpu

HPCTransCompile: An AI Compiler Generated Dataset for High-Performance CUDA Transpilation and LLM Preliminary Exploration

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

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high performance computing on graphics processing units: hgpu.org

The Comparisons of OpenCL and OpenMP Computing Paradigm

A Quantitative Comparison of Emulated Shared Memory Architectures to Current Multicore CPUs and GPUs

Applications of Many-Core Technologies to On-line Event Reconstruction in High Energy Physics Experiments

Comparative Study of High Performance Computing Using Multi-core Parallel Systems

Divergence Analysis

SESH framework: A Space Exploration Framework for GPU Application and Hardware Codesign

Benchmarking Parallel Performance on Many-Core Processors

The Future of Accelerator Programming: Abstraction, Performance or Can We Have Both?

Hybrid Programming using OpenSHMEM and OpenACC

Evaluating the Performance and Energy Efficiency of N-Body Codes on Multi-Core CPUs and GPUs

Exploring Graphics Processing Unit (GPU) Resource Sharing Efficiency for High Performance Computing

Dynamic Partitioning-based JPEG Decompression on Heterogeneous Multicore Architectures

Recent source codes

HPCTransCompile: An AI Compiler Generated Dataset for High-Performance CUDA Transpilation and LLM Preliminary Exploration

chemtrain: Training Molecular Dynamics Potentials in JAX

microSYCL: SYCL micro-benchmarks repository

XaaS containers

SYCL Container

CASS: Cuda-Amd aSSembly

Cluser of smartphones for edge computing application using TensorFlow

CFAL-bench

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

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