high performance computing on graphics processing units: hgpu.org

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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

Porting to the Intel Xeon Phi: Opportunities and Challenges

C. Rosales

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, Intel Phi, MPI, nVidia, Optimization, Performance

September 15, 2013 by hgpu

D5.5.2 – Architectural Techniques to exploit SLACK & ACCURACY trade-offs

S. Kaxiras, G. Keramidas, K. Koukos

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Tags: Benchmarking, Memory, Power-efficient computing

September 6, 2013 by hgpu

Optimizing the MapReduce Framework on Intel Xeon Phi Coprocessor

Mian Lu, Lei Zhang, Huynh Phung Huynh, Zhongliang Ong, Yun Liang, Bingsheng He, Rick Siow Mong Goh, Richard Huynh

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Tags: Benchmarking, Computer science, Intel Phi, MapReduce

September 4, 2013 by hgpu

Throughput-Oriented Analytical Models for Performance Estimation on Programmable Hardware Accelerators

Junjie Lai

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Tags: Analytical model, Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 680, Thesis

August 28, 2013 by hgpu

Performance Evaluation of Intel Xeon Phi Coprocessor using XKaapi

Joao V. F. Lima, Nicolas Maillard, Franciois Broquedis, Thierry Gautier, Bruno Raffin

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

August 26, 2013 by hgpu

On Benchmarking the Matrix Multiplication Algorithm using OpenMP, MPI and CUDA Programming Languages

Muhammed Al-Mulhem, Abdulah AlDhamin, Raed Al-Shaikh

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Tags: Algorithms, Benchmarking, Bioinformatics, Computer science, CUDA, Linear Algebra, Matrix multiplication, MPI, nVidia, nVidia GeForce GTX 460

July 19, 2013 by hgpu

Benchmarking Intel Xeon Phi to Guide Kernel Design

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

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

July 14, 2013 by hgpu

Comparative study of parallel programming models for multicore computing

Akhtar Ali

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Tags: Benchmarking, Computer science, DSP, Heterogeneous systems, nVidia, OpenCL, OpenMP, Tesla M2050, Thesis

July 7, 2013 by hgpu

Towards Rapid Prototyping of Parallel and HPC Applications (GPU Focus)

Mohammed S. Al-Mahfoudh

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 440, Thesis

June 28, 2013 by hgpu

GPUburn: A System to Test and Mitigate GPU Hardware Failures

David Defour, Eric Petit

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Tags: Benchmarking, Computer science, CUDA, Fault tolerance, nVidia, OpenCL, Tesla D870

June 2, 2013 by hgpu

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

GigaAPI for GPU Parallelization

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

Advances in Semantic Patching for HPC-oriented Refactorings with Coccinelle

DuoReduce: MLIR's benchmark

Hardware-Assisted Software Testing and Debugging for Heterogeneous Computing

Shamrock: Multi-GPU hydrodynamics for astrophysics

The Shamrock code: I- Smoothed Particle Hydrodynamics on GPUs

LLMPerf: GPU Performance Modeling meets Large Language Models

Hercules: A Compiler for Productive Programming of Heterogeneous Systems

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high performance computing on graphics processing units: hgpu.org

BenchFriend: Correlating the Performance of GPU Benchmarks

Processing MPI Derived Datatypes on Noncontiguous GPU-Resident Data

Porting to the Intel Xeon Phi: Opportunities and Challenges

D5.5.2 – Architectural Techniques to exploit SLACK & ACCURACY trade-offs

Optimizing the MapReduce Framework on Intel Xeon Phi Coprocessor

Throughput-Oriented Analytical Models for Performance Estimation on Programmable Hardware Accelerators

Performance Evaluation of Intel Xeon Phi Coprocessor using XKaapi

On Benchmarking the Matrix Multiplication Algorithm using OpenMP, MPI and CUDA Programming Languages

Benchmarking Intel Xeon Phi to Guide Kernel Design

Comparative study of parallel programming models for multicore computing

Towards Rapid Prototyping of Parallel and HPC Applications (GPU Focus)

GPUburn: A System to Test and Mitigate GPU Hardware Failures

Recent source codes

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

GigaAPI: a user-space API that simplifies multi-GPU programming, bridging the gap between the capabilities of parallel GPU systems and the ability of developers to harness their full potential

Coccinelle: a C code transformation engine using SmPL for matches, refactorings, and bug fixing

DuoReduce: MLIR's benchmark

Shamrock: Multi-GPU hydrodynamics for astrophysics

LLMPerf: GPU Performance Modeling meets Large Language Models

Hercules: A Compiler for Productive Programming of Heterogeneous Systems

Celerity Runtime: High-level C++ for Accelerator Clusters

wgpy: WebGL accelerated numpy-compatible array library for web browser

Microbenchmarking OpenMP target offload with Catch2

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