high performance computing on graphics processing units: hgpu.org

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hgpu.org » Applications » Image and Signal Processing

HIPAcc: A Domain-Specific Language and Compiler for Image Processing

Richard Membarth, Oliver Reiche, Frank Hannig, Jurgen Teich, Mario Korner, Wieland Eckert

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Tags: Algorithms, AMD Radeon R9 290X, ARM, ATI, Compilers, Computer science, CUDA, Heterogeneous systems, Image processing, Intel Xeon Phi, nVidia, OpenCL, Package, Tesla K20

November 19, 2016 by hgpu

Executing Dynamic Data Rate Actor Networks on OpenCL Platforms

Jani Boutellier, Ilkka Hautala

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Tags: ATI, ATI Radeon HD 7750, Computer science, Heterogeneous systems, OpenCL, Signal processing

November 13, 2016 by hgpu

Vispark: GPU-Accelerated Distributed Visual Computing Using Spark

Woohyuk Choi, Sumin Hong, Won-Ki Jeong

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Tags: Clustering, Computer science, CUDA, Distributed computing, DSL, GPU cluster, Image processing, MapReduce, nVidia, nVidia GeForce GTX Titan, Python, Rendering, Spark

November 8, 2016 by hgpu

Programming Heterogeneous Systems from an Image Processing DSL

Jing Pu, Steven Bell, Xuan Yang, Jeff Setter, Stephen Richardson, Jonathan Ragan-Kelley, Mark Horowitz

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Tags: ARM, Computer science, Computer vision, CUDA, DSL, FPGA, Image processing, nVidia, nVidia Jetson TK1, OpenGL, Package

November 1, 2016 by hgpu

Combining Belief Propagation and Successive Cancellation List Decoding of Polar Codes on a GPU Platform

Sebastian Cammerer, Benedikt Leible, Matthias Stahl, Jakob Hoydis, Stephan ten Brink

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 980 Ti, Signal processing

September 30, 2016 by hgpu

Efficient dictionary learning implementation on the GPU using OpenCL

Paul Irofti

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Tags: Algorithms, Computer science, Machine learning, OpenCL, Signal processing

September 22, 2016 by hgpu

Finding faint HI structure in and around galaxies: scraping the barrel

D. Punzo, J.M. van der Hulst, J.B.T.M. Roerdink

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Tags: Astrophysics, Filtering, Image processing, nVidia, nVidia GeForce GTX 860 M, OpenGL, OpenMP, Package, Visualization

September 17, 2016 by hgpu

An Implementation of Real-Time Phased Array Radar Fundamental Functions on a DSP-Focused, High-Performance, Embedded Computing Platform

Xining Yu, Yan Zhang, Ankit Patel, Allen Zahrai, Mark Weber

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Tags: DSP, Filtering, OpenCL, OpenMP, Signal processing

September 10, 2016 by hgpu

Parallel Dictionary Learning Algorithms for Sparse Representations

Paul Irofti

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Tags: ATI, ATI FirePro V8800, Computer science, Data mining, Machine learning, OpenCL, Signal processing, Thesis

September 5, 2016 by hgpu

Fast Multidimensional Image Processing with OpenCL

Daniel Oliveira Dantas, Helton Danilo Passos Leal, Davy Oliveira Barros Sousa

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Tags: AMD Radeon R9 270X, ATI, CUDA, GLSL, Image processing, OpenCL, Package

August 23, 2016 by hgpu

Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising

Kai Zhang, Wangmeng Zuo, Yunjin Chen, Deyu Meng, Lei Zhang

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Tags: CNN, CUDA, Deep learning, Image processing, Matlab, nVidia, nVidia GeForce GTX Titan X, Package, Signal denoising

August 18, 2016 by hgpu

A Gb/s Parallel Block-based Viterbi Decoder for Convolutional Codes on GPU

Hao Peng, Rongke Liu, Yi Hou, Ling Zhao

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 980, Signal processing

August 4, 2016 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

Applications

HIPAcc: A Domain-Specific Language and Compiler for Image Processing

Executing Dynamic Data Rate Actor Networks on OpenCL Platforms

Vispark: GPU-Accelerated Distributed Visual Computing Using Spark

Programming Heterogeneous Systems from an Image Processing DSL

Combining Belief Propagation and Successive Cancellation List Decoding of Polar Codes on a GPU Platform

Efficient dictionary learning implementation on the GPU using OpenCL

Finding faint HI structure in and around galaxies: scraping the barrel

An Implementation of Real-Time Phased Array Radar Fundamental Functions on a DSP-Focused, High-Performance, Embedded Computing Platform

Parallel Dictionary Learning Algorithms for Sparse Representations

Fast Multidimensional Image Processing with OpenCL

Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising

A Gb/s Parallel Block-based Viterbi Decoder for Convolutional Codes on GPU

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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