high performance computing on graphics processing units: hgpu.org

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hgpu.org » Applications

Fast Gather-based Construction of Stereoscopic Images Using Reprojection

Marries van de Hoef, Bas Zalmstra

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Tags: ATI, ATI Radeon HD 5670, ATI Radeon HD 5850, Benchmarking, Cg, Image processing, nVidia, nVidia GeForce 9600 GT, OpenGL, Package

November 18, 2011 by hgpu

The Multi2Sim Simulation Framework: A CPU-GPU Model for Heterogeneous Computing

Rafael Ubal, Julio Sahuquillo, Salvador Petit, Pedro Lopez, Zhongliang Chen, David R. Kaeli

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Tags: ATI, ATI Radeon HD 5870, Computer science, Heterogeneous systems, OpenCL, Operating systems, Package

November 18, 2011 by hgpu

Optimizing the multipole-to-local operator in the fast multipole method for graphical processing units

Toru Takahashi1, Cris Cecka, William Fong, Eric Darve

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Tags: Algorithms, CUDA, Fast multipole method, nVidia, Package, Physics, Tesla C1060, Tesla C2050

November 18, 2011 by hgpu

Compilation for Heterogeneous Computing: Automating Analyses, Transformations and Decisions

Serge Guelton, Francois Irigoin, Ronan Keryell

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Tags: Code generation, Computer science, CUDA, FPGA, Heterogeneous systems, nVidia, nVidia Quadro FX 2700 M, Package, Signal processing

November 17, 2011 by hgpu

Prospects for scalable 3D FFTs on heterogeneous exascale systems

Chris McClanahan, Kent Czechowski, Casey Battaglino, Kartik Iyer, P.-K. Yeung, Richard Vuduc

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Tags: Analytical model, Benchmarking, Computer science, CUDA, FFT, GPU cluster, Heterogeneous systems, nVidia, OpenMPI, Package, Tesla M2070

November 16, 2011 by hgpu

An Ultrafast Scalable Many-core Motif Discovery Algorithm for Multiple GPUs

Yongchao Liu, Bertil Schmidt, Douglas L. Maskell

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Tags: Algorithms, Benchmarking, Biology, CUDA, GPU cluster, MPI, nVidia, OpenMP, Package, Tesla S2050

November 15, 2011 by hgpu

gSLIC: a real-time implementation of SLIC superpixel segmentation

Carl Yuheng Ren, Ian Reid

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Tags: Clustering, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 460, Package

November 15, 2011 by hgpu

B-CALM: An open-source GPU-based 3D-FDTD with multi-pole dispersion for plasmonics

Pierre Wahl, Dany-Sebastien Ly-Gagnon, Christof Debaes, David A.B. Miller, Hugo Thienpont

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Tags: Algorithms, FDTD, Finite-difference time-domain, Mesoscale and Nanoscale Physics, nVidia, Optics, Package, Physics, Tesla C1060

November 14, 2011 by hgpu

Fast Level Set Segmentation of Biomedical Images using Graphics Processing Units

Hormuz Mostofi

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Tags: Algorithms, Computer vision, CUDA, Image processing, Medicine, nVidia, nVidia GeForce 8600 M GT, Package

November 13, 2011 by hgpu

Efficient GPU Implementation for Particle in Cell Algorithm

Rejith George Joseph, Girish Ravunnikutty, Sanjay Ranka, Eduardo D'Azevedo, Scott Klasky

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Tags: Algorithms, CUDA, Electrodynamics, nVidia, Package, Particle-in-cell methods, Physics, Plasma physics, Tesla T10

November 13, 2011 by hgpu

rCUDA: Reducing the number of GPU-based accelerators in high performance clusters

J. Duato, Pena, A.J. a, F. Silla, R. Mayo, E.S. Quintana-Orti

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Tags: Computer science, CUDA, Distributed computing, Energy-efficient computing, nVidia, Package, PC cluster, Tesla C1060

November 12, 2011 by hgpu

GSNP: A DNA Single-Nucleotide Polymorphism Detection System with GPU Acceleration

Mian Lu, Jiuxin Zhao, Qiong Luo, Bingqiang Wang, Shaohua Fu, Zhe Lin

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Tags: Bioinformatics, Biology, Compression, nVidia, Package, Sorting, Tesla M2050

November 12, 2011 by hgpu

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

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high performance computing on graphics processing units: hgpu.org

Packages

Fast Gather-based Construction of Stereoscopic Images Using Reprojection

The Multi2Sim Simulation Framework: A CPU-GPU Model for Heterogeneous Computing

Optimizing the multipole-to-local operator in the fast multipole method for graphical processing units

Compilation for Heterogeneous Computing: Automating Analyses, Transformations and Decisions

Prospects for scalable 3D FFTs on heterogeneous exascale systems

An Ultrafast Scalable Many-core Motif Discovery Algorithm for Multiple GPUs

gSLIC: a real-time implementation of SLIC superpixel segmentation

B-CALM: An open-source GPU-based 3D-FDTD with multi-pole dispersion for plasmonics

Fast Level Set Segmentation of Biomedical Images using Graphics Processing Units

Efficient GPU Implementation for Particle in Cell Algorithm

rCUDA: Reducing the number of GPU-based accelerators in high performance clusters

GSNP: A DNA Single-Nucleotide Polymorphism Detection System with GPU Acceleration

Recent source codes

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

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