high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications

Fast and Memory Efficient GPU-Based Rendering of Tensor Data

Mario Hlawitschka, Sebastian Eichelbaum, Gerik Scheuermann

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Tags: Computer science, OpenGL, Physics, Rendering, Visualization

February 27, 2011 by hgpu

Efficient hierarchical parallel genetic algorithms using grid computing

Dudy Lim, Yew-Soon Ong, Yaochu Jin, Bernhard Sendhoff, Bu-Sung Lee

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Tags: Algorithms, Computer science, Genetic programming, Grid

February 27, 2011 by hgpu

GPU ray casting of virtual globes

Patrick Cozzi, Frank Stoner

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Tags: 3D Graphics and Realism, Computer science, nVidia, nVidia GeForce 8400 GS, Rendering, Visualization

February 27, 2011 by hgpu

Data Mining and Machine Learning in Astronomy

Nicholas M. Ball, Robert J. Brunner

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Tags: Astrophysics, Cosmology and Extragalactic Astrophysics, CUDA, Data mining, Instrumentation and Methods for Astrophysics, nVidia, Review

February 27, 2011 by hgpu

Data Buffering Optimization Methods toward a Uniform Programming Interface for GPU-based Applications

Shinichi Yamagiwa, Leonel Sousa, Diogo Antao

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Tags: Computer science, DirectX, nVidia, nVidia GeForce 7400 GO, OpenGL, Programming techniques

February 27, 2011 by hgpu

A Method for Accelerating Bronchoscope Tracking Based on Image Registration by GPGPU

Takamasa Sugiura, Daisuke Deguchi, Takayuki Kitasaka, Kensaku Mori, Yasuhito Suenaga

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Tags: Computed tomography, CT, CUDA, Image registration, Medicine, nVidia, nVidia GeForce 8800 GTX

February 27, 2011 by hgpu

CUDAlign: using GPU to accelerate the comparison of megabase genomic sequences

Edans Flavius O. Sandes, Alba Cristina M.A. de Melo

Tags: Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GTX 280, Sequence alignment, Smith-Waterman algorithm

February 27, 2011 by hgpu

Size Matters: Space/Time Tradeoffs to Improve GPGPU Applications Performance

Abdullah Gharaibeh, Matei Ripeanu

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Tags: Bioinformatics, Biology, Computational biology, CUDA, nVidia, nVidia GeForce 8800 GTX, Package, Sequence alignment, Short read mapping, Suffix trees

February 27, 2011 by hgpu

Accelerating CUDA Graph Algorithms at Maximum Warp

Sungpack Hong, Sang Kyun Kim, Tayo Oguntebi, Kunle Olukotun

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 275, Package, Performance, Programming techniques

February 27, 2011 by hgpu

A Domain-Specific Approach To Heterogeneous Parallelism

Hassan Chafi, Arvind K. Sujeeth, Kevin J. Brown, HyoukJoong Lee, Anand R. Atreya, Kunle Olukotun

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Tags: Code generation, Compilers, Computer science, CUDA, Heterogeneous systems, High-level Languages, nVidia, nVidia GeForce GTX 275

February 27, 2011 by hgpu

StarPU: a Runtime System for Scheduling Tasks over Accelerator-Based Multicore Machines

Cedric Augonnet, Samuel Thibault, Raymond Namyst

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Tags: Computer science, CUDA, Distributed computing, nVidia, nVidia Quadro FX 4600, nVidia Quadro FX 5800, Package, Performance

February 26, 2011 by hgpu

A Tuning Framework for Software-Managed Memory Hierarchies

Manman Ren, Ji Young Park, Mike Houston, Alex Aiken, William J. Dally

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Tags: Algorithms, Cell processor, Compilers, Computer science, Optimization, Performance, Playstation, Programming Languages

February 26, 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

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

Fast and Memory Efficient GPU-Based Rendering of Tensor Data

Efficient hierarchical parallel genetic algorithms using grid computing

GPU ray casting of virtual globes

Data Mining and Machine Learning in Astronomy

Data Buffering Optimization Methods toward a Uniform Programming Interface for GPU-based Applications

A Method for Accelerating Bronchoscope Tracking Based on Image Registration by GPGPU

CUDAlign: using GPU to accelerate the comparison of megabase genomic sequences

Size Matters: Space/Time Tradeoffs to Improve GPGPU Applications Performance

Accelerating CUDA Graph Algorithms at Maximum Warp

A Domain-Specific Approach To Heterogeneous Parallelism

StarPU: a Runtime System for Scheduling Tasks over Accelerator-Based Multicore Machines

A Tuning Framework for Software-Managed Memory Hierarchies

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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