high performance computing on graphics processing units: hgpu.org

hgpu.org » Performance

Batch Method for Efficient Resource Sharing in Real-time Multi-GPU Systems

Uri Verner, Avi Mendelson, Assaf Schuster

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Tags: Computer science, CUDA, nVidia, OpenCL, Performance, Task scheduling, Tesla C2050, Tesla K10

November 4, 2013 by hgpu

A Locality-Aware Memory Hierarchy for Energy-Efficient GPU Architectures

Minsoo Rhu, Michael Sullivan, Jingwen Leng, Mattan Erez

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Tags: Computer science, GPGPU-sim, Memory, Performance, Prefetch

October 29, 2013 by hgpu

Online Performance Projection for Clusters with Heterogeneous GPUs

Lokendra S. Panwar, Ashwin M. Aji, Jiayuan Mengz, Pavan Balajiy, Wu-chun Feng

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Tags: ATI, ATI Radeon HD 5870, ATI Radeon HD 7970, Computer science, GPGPU-sim, GPU cluster, Heterogeneous systems, nVidia, OpenCL, Performance, Tesla C1060, Tesla C2050

October 25, 2013 by hgpu

An Empirical Study of Intel Xeon Phi

Jianbin Fang, Ana Lucia Varbanescu, Henk Sips, Lilun Zhang, Yonggang Che, Chuanfu Xu

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

October 25, 2013 by hgpu

Modeling system for GPU parallel tasks performance simulation

A.Y.Doroshenko, K.A. Zhereb, O.G.Beketov, M.V. Gnynjuk

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Tags: Computer science, CUDA, Heterogeneous systems, Java, nVidia, nVidia GeForce GT 650 M, Performance

October 24, 2013 by hgpu

Concurrent kernel execution on Graphic Processing Units

Adrien Cassagne, Aurelien George, Benjamin Lorendeau, Jean-Charles Papin, Antoine Rougier

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 660, nVidia Quadro 4000, OpenCL, Performance, Thesis

October 21, 2013 by hgpu

OpenACC-based Snow Simulation

Magnus Alvestad Mikalsen

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, OpenACC, OpenCL, Performance, Tesla C2070, Tesla K20, Thesis

October 18, 2013 by hgpu

Understanding and Modeling the Synchronization Cost in the GPU Architecture

James T. Letendre

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, Performance, Tesla C2075, Thesis

October 17, 2013 by hgpu

Empirical performance modeling of GPU kernels using active learning

Prasanna Balaprakash, Karl Rupp, Azamat Mametjanov, Robert B. Gramacy, Paul D. Hovland, Stefan M. Wild

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Tags: Algorithms, ATI, ATI Radeon HD 7970, Computer science, CUDA, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 470, OpenCL, Performance, Tesla C2050, Tesla K20

October 17, 2013 by hgpu

Performance Comparison of GPU, DSP and FPGA implementations of image processing and computer vision algorithms in embedded systems

Egil Fykse

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Tags: Benchmarking, Computer science, Computer vision, CUDA, DSP, FPGA, Image processing, nVidia, nVidia GeForce GTX 660 Ti, nVidia Quadro 1000 M, OpenCV, Performance, Thesis

October 15, 2013 by hgpu

Performance Analysis of a Large Memory Application on Multiple Architectures

P.M.Kogge

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Tags: Benchmarking, Heterogeneous systems, nVidia, nVidia Tesla, Performance

October 9, 2013 by hgpu

GPU-TLS: An Efficient Runtime for Speculative Loop Parallelization on GPUs

Chenggang Zhang, Guodong Han, Cho-Li Wang

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 580, Performance, Tesla M2050

September 27, 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

Batch Method for Efficient Resource Sharing in Real-time Multi-GPU Systems

A Locality-Aware Memory Hierarchy for Energy-Efficient GPU Architectures

Online Performance Projection for Clusters with Heterogeneous GPUs

An Empirical Study of Intel Xeon Phi

Modeling system for GPU parallel tasks performance simulation

Concurrent kernel execution on Graphic Processing Units

OpenACC-based Snow Simulation

Understanding and Modeling the Synchronization Cost in the GPU Architecture

Empirical performance modeling of GPU kernels using active learning

Performance Comparison of GPU, DSP and FPGA implementations of image processing and computer vision algorithms in embedded systems

Performance Analysis of a Large Memory Application on Multiple Architectures

GPU-TLS: An Efficient Runtime for Speculative Loop Parallelization on GPUs

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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