high performance computing on graphics processing units: hgpu.org

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Exploring GPGPU workloads: Characterization methodology, analysis and microarchitecture evaluation implications

Nilanjan Goswami, Ramkumar Shankar, Madhura Joshi, Tao Li

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Tags: Benchmarking, Computer science, CUDA, nVidia, Performance, PTX

April 4, 2011 by hgpu

A Static Task Partitioning Approach for Heterogeneous Systems Using OpenCL

Dominik Grewe, Michael O'Boyle

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Tags: ATI, ATI Radeon HD 5970, Benchmarking, Computer science, Heterogeneous systems, OpenCL, Package, Task scheduling

April 4, 2011 by hgpu

Implementing the Himeno benchmark with CUDA on GPU clusters

Everett H. Phillips, Massimiliano Fatica

Tags: Benchmarking, Computer science, CUDA, GPU cluster, nVidia, Performance, Tesla C1060

March 16, 2011 by hgpu

Benchmarking GPU Devices with N-Body Simulations

Daniel P. Playne, Mitchell Johnson, Kenneth A. Hawick

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Tags: Benchmarking, Computer science, CUDA, N-body simulation, nVidia, nVidia GeForce 9400 M, nVidia GeForce 9600 M GT

December 29, 2010 by hgpu

Rodinia: A benchmark suite for heterogeneous computing

Shuai Che, Michael Boyer, Jiayuan Meng, David Tarjan, Jeremy W. Sheaffer, Sang-Ha Lee, Kevin Skadron

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, OpenMP

November 19, 2010 by hgpu

Evolution of thread-level parallelism in desktop applications

Geoffrey Blake, Ronald G. Dreslinski, Trevor Mudge, Krisztian Flautner

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Tags: Benchmarking, Computer science, Measurement techniques, nVidia, nVidia GeForce GT 120, nVidia GeForce GTX 285, nVidia ION

November 7, 2010 by hgpu

The Scalable Heterogeneous Computing (SHOC) benchmark suite

Anthony Danalis,Gabriel Marin,Collin McCurdy,Jeremy S. Meredith,Philip C. Roth,Kyle Spafford,Vinod Tipparaju,Jeffrey S. Vetter

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Tags: ATI, ATI Radeon HD 5770, ATI Radeon HD 5870, ATI Stream, Benchmarking, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 8800 GT, nVidia GeForce 8800 GTS, nVidia GeForce 8800 GTX, nVidia GeForce 9400 M, OpenCL, Package, Performance, Tesla C1060

November 5, 2010 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

Exploring GPGPU workloads: Characterization methodology, analysis and microarchitecture evaluation implications

A Static Task Partitioning Approach for Heterogeneous Systems Using OpenCL

Implementing the Himeno benchmark with CUDA on GPU clusters

Benchmarking GPU Devices with N-Body Simulations

Rodinia: A benchmark suite for heterogeneous computing

Evolution of thread-level parallelism in desktop applications

The Scalable Heterogeneous Computing (SHOC) benchmark suite

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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