high performance computing on graphics processing units: hgpu.org

hgpu.org » Benchmarking

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

Regression Modelling of Power Consumption for Heterogeneous Processors

Tahir Diop

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Tags: Benchmarking, Computer science, Energy-efficient computing, Heterogeneous systems, nVidia, OpenCL, Tesla M2090, Thesis

November 27, 2013 by hgpu

Bohrium: Unmodified NumPy Code on CPU, GPU, and Cluster

Mads R. B. Kristensen, Simon A. F. Lund, Troels Blum, Kenneth Skovhede, Brian Vinter

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Tags: ATI, ATI Radeon HD 7850, Benchmarking, Computer science, GPU cluster, nVidia, nVidia GeForce GTX 680, OpenCL, Python

November 22, 2013 by hgpu

Performance and Power Comparisons Between Fermi and Cypress GPUs

Ying Zhang

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Tags: ATI, ATI Radeon HD 5870, Benchmarking, Computer science, CUDA, Energy-efficient computing, nVidia, nVidia GeForce GTX 580, OpenCL, Performance, Thesis

November 18, 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

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

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

Egil Fykse

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Source codes

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

Compiling a High-level Directive-Based Programming Model for GPGPUs

Xiaonan Tian, Rengan Xu, Yonghong Yan, Zhifeng Yun, Sunita Chandrasekaran, Barbara Chapman

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Tags: Benchmarking, Computer science, nVidia, OpenACC, Tesla K20

September 30, 2013 by hgpu

Data-parallel Acceleration of PARSEC Black-Scholes Benchmark

August Andren, Patrik Hagernas

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Tags: Benchmarking, Computer science, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 680, OpenACC, Tesla C2050, Tesla M2090

September 30, 2013 by hgpu

BenchFriend: Correlating the Performance of GPU Benchmarks

Shuai Che, Kevin Skadron

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Tags: Benchmarking, Computer science, CUDA, GPGPU-sim, nVidia, Tesla C2050, Tesla K20

September 23, 2013 by hgpu

Processing MPI Derived Datatypes on Noncontiguous GPU-Resident Data

John Jenkins, James Dinan, Pavan Balaji, Tom Peterka, Nagiza F. Samatova, Rajeev Thakur

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Tags: Algorithms, Benchmarking, Computer science, CUDA, MPI, nVidia, Tesla C2050

September 23, 2013 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

See all packages

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high performance computing on graphics processing units: hgpu.org

Benchmarking Parallel Performance on Many-Core Processors

Regression Modelling of Power Consumption for Heterogeneous Processors

Bohrium: Unmodified NumPy Code on CPU, GPU, and Cluster

Performance and Power Comparisons Between Fermi and Cypress GPUs

An Empirical Study of Intel Xeon Phi

Understanding and Modeling the Synchronization Cost in the GPU Architecture

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

Compiling a High-level Directive-Based Programming Model for GPGPUs

Data-parallel Acceleration of PARSEC Black-Scholes Benchmark

BenchFriend: Correlating the Performance of GPU Benchmarks

Processing MPI Derived Datatypes on Noncontiguous GPU-Resident Data

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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