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A CPU-GPU Hybrid Runtime for the Aeminium Language

Alcides Fonseca

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Tags: Compilers, Computer science, Java, MapReduce, nVidia, nVidia GeForce GTX 285, OpenCL, Optimization, Package, Sorting, Thesis

November 10, 2011 by hgpu

GrAVity: a massively parallel antivirus engine

Giorgos Vasiliadis, Sotiris Ioannidis

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 295, Security

November 9, 2011 by hgpu

Parallel Implementation of Otsu’s Binarization Approach on GPU

Brij Mohan Singh, Rahul Sharma, Ankush Mittal, Debashish Ghosh

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Tags: Algorithms, Computer science, Computer vision, CUDA, Image processing, nVidia, nVidia GeForce 9500 GT, Pattern recognition

November 9, 2011 by hgpu

Parallel Implementation of Souvola’s Binarization Approach on GPU

Brij Mohan Singh, Rahul Sharma, Ankush Mittal, Debashish Ghosh

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Tags: Algorithms, Computer science, Computer vision, CUDA, Image processing, nVidia, nVidia GeForce 9500 GT, Pattern recognition

November 9, 2011 by hgpu

Low Complexity Corner Detector Using CUDA for Multimedia Applications

Rajat Phull, Pradip Mainali, Qiong Yang, Patrice Rondao Alface, Henk Sips

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 280

November 9, 2011 by hgpu

Effects of GPU and CPU Loads on Performance of CUDA Applications

Maksim Bobrov, Roy Melton, Stanislaw Radziszowski, Marcin Lukowiak

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Tags: AES, Algorithms, Computer science, CUDA, Hashing, nVidia, nVidia GeForce GTX 285, Performance, Security

November 9, 2011 by hgpu

Large data visualization on distributed memory multi-GPU clusters

Thomas Fogal, Hank Childs, Siddharth Shankar, Jens Kruger, R. Daniel Bergeron, Philip Hatcher

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Tags: Algorithms, Computer science, GLSL, GPU cluster, nVidia, nVidia GeForce 8800 GTX, nVidia Quadro FX 5800, OpenGL, Performance, Rendering, Visualization

November 9, 2011 by hgpu

Automatic transformation and optimization of applications on GPUs and GPU clusters

Wenjing Ma

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Tags: Algorithm optimization, Algorithms, Benchmarking, Code generation, Computer science, CUDA, Data mining, GPU cluster, Heterogeneous systems, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce 9800 GX2, Optimization, Tesla T10, Thesis

November 9, 2011 by hgpu

GPU-based ray casting of stacked out-of-core height fields

Christopher Lux, Bernd Frohlich

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Tags: Computer science, GLSL, nVidia, nVidia GeForce GTX 480, OpenCL, OpenGL, Rendering, Visualization

November 9, 2011 by hgpu

Parallel Implementation of Niblack’s Binarization Approach on CUDA

Brij Mohan Singh, Rahul Sharma, Ankush Mittal, Debashish Ghosh

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Tags: Algorithms, Computer science, Computer vision, CUDA, Image processing, nVidia, nVidia GeForce 9500 GT, Pattern recognition

November 9, 2011 by hgpu

PATUS: A Code Generation and Auto-Tuning Framework For Parallel Stencil Computations

Matthias Christen, Olaf Schenk, Helmar Burkhart

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Tags: Code generation, Computer science, CUDA, nVidia, Optimization, Package, Tesla C2050

November 8, 2011 by hgpu

GPU Cluster with MATLAB

A. Guillen, M. Garcia, L. J. Herrera, H. Pomares, I. Rojas

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Tags: Computer science, CUDA, GPU cluster, Heterogeneous systems, MPI, Nearest neighbour, nVidia, nVidia GeForce 8400 GS, nVidia GeForce 9800 GTX, nVidia GeForce GTS 450

November 8, 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

A CPU-GPU Hybrid Runtime for the Aeminium Language

GrAVity: a massively parallel antivirus engine

Parallel Implementation of Otsu’s Binarization Approach on GPU

Parallel Implementation of Souvola’s Binarization Approach on GPU

Low Complexity Corner Detector Using CUDA for Multimedia Applications

Effects of GPU and CPU Loads on Performance of CUDA Applications

Large data visualization on distributed memory multi-GPU clusters

Automatic transformation and optimization of applications on GPUs and GPU clusters

GPU-based ray casting of stacked out-of-core height fields

Parallel Implementation of Niblack’s Binarization Approach on CUDA

PATUS: A Code Generation and Auto-Tuning Framework For Parallel Stencil Computations

GPU Cluster with MATLAB

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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