high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications » Image and Signal Processing

Digital Signal Processing using Stream High Performance Computing: A 512-input Broadband Correlator for Radio Astronomy

J. Kocz, L.J Greenhill, B.R. Barsdell, D. Price, G. Bernardi, S. Bourke, M.A. Clark, J. Craig, M. Dexter, J. Dowell, T. Eftekhari, S. Ellingson, G. Hallinan, J. Hartman, A. Jameson, D. MacMahon, G. Taylor, F. Schinzel, D. Werthimer

View

Download (PDF)

Source codes

Tags: Astrophysics, CUDA, FPGA, GPU cluster, Heterogeneous systems, Instrumentation and Methods for Astrophysics, nVidia, Package, Signal processing, Tesla K20

January 10, 2015 by hgpu

Exploring GPU Memory Performance Using Digital Image Processing Algorithms

Puya Memarzia, Farshad Khunjush

View

Download (PDF)

Tags: Benchmarking, Computer science, CUDA, Image processing, nVidia, nVidia GeForce GTX 570

January 10, 2015 by hgpu

Computationally Efficient Implementation of a Hamming Code Decoder using a Graphics Processing Unit

Shohidul Islam, Cheol-Hong Kim, Jong-Myon Kim

View

Download (PDF)

Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 560, Signal processing

December 26, 2014 by hgpu

A Domain-specific Language to Facilitate Software Defined Radio Parallel Executable Patterns Deployment on Heterogeneous Architectures

Lerato J. Mohapi, Simon Winberg, Michael Inggs

View

Download (PDF)

Tags: Algorithms, CUDA, DSP, FPGA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, OpenCL, Signal processing

December 22, 2014 by hgpu

SignalPU: A programming model for DSP applications on parallel and heterogeneous clusters

Farouk Mansouri, Sylvain Huet, Dominique Houzet

View

Download (PDF)

Tags: Algorithms, CUDA, DSP, Heterogeneous systems, nVidia, nVidia GeForce GT 610, nVidia GeForce GTX Titan, nVidia Quadro 4000, Signal processing

December 20, 2014 by hgpu

Risk Estimation Without Using Stein’s Lemma — Application to Image Denoising

Sagar Venkatesh Gubbi, Chandra Sekhar Seelamantula

View

Download (PDF)

Source codes

Tags: ATI, ATI Radeon HD 7950, Computer vision, Image processing, OpenCL, Package, Signal denoising

December 9, 2014 by hgpu

Parallel GPU Processing for Fast Radio Signal Propagation Computation in GRASS-RaPlaT

Igor Ozimek, Andrej Hrovat, Andrej Vilhar, Tomaz Javornik

View

Download (PDF)

Tags: nVidia, nVidia GeForce GTX 580, OpenCL, Physics, Signal processing

December 7, 2014 by hgpu

OpenCL Based High-Quality HEVC Motion Estimation on GPU

Fan Wang, Dajiang Zhou, Satoshi Goto

View

Download (PDF)

Tags: AMD Radeon R9 290, ATI, Compression, H.265, Image processing, OpenCL

December 3, 2014 by hgpu

GPU Declarative Framework

Robert W. Senser, Jr.

View

Download (PDF)

Tags: AMD Radeon R9 270, ATI, Code generation, Computer science, Filtering, Image processing, Matrix inversion, nVidia, OpenCL, Sorting, Tesla S2050, Tesla T20, Thesis

December 1, 2014 by hgpu

A GPU-based framework for efficient image processing

Per Karlsson

View

Download (PDF)

Tags: CUDA, GLSL, Image processing, nVidia, nVidia GeForce GTX 760, OpenCL, OpenGL, Python, Thesis

November 20, 2014 by hgpu

FPGA: An Efficient And Promising Platform For Real-Time Image Processing Applications

Sparsh Mittal, Saket Gupta, Sudeb Dasgupta

View

Download (PDF)

Tags: DSP, FPGA, Image processing, survey

November 19, 2014 by sparsh0mittal

The Implementation of a Real-Time Polyphase Filter

Karel Adamek, Jan Novotny, Wes Armour

View

Download (PDF)

Tags: CUDA, Intel Xeon Phi, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 750 Ti, Performance, Signal processing, Tesla K40

November 16, 2014 by hgpu

CuPBoP-AMD: Extending CUDA to AMD Platforms

CuPBoP: Making CUDA a Portable Language

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

Automated Deep Learning Optimization via DSL-Based Source Code Transformation

ROCm's implementation of Gromacs

GROMACS on AMD GPU-Based HPC Platforms: Using SYCL for Performance and Portability

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

Experiences with implementing Kokkos’ SYCL backend

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

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Applications

Digital Signal Processing using Stream High Performance Computing: A 512-input Broadband Correlator for Radio Astronomy

Exploring GPU Memory Performance Using Digital Image Processing Algorithms

Computationally Efficient Implementation of a Hamming Code Decoder using a Graphics Processing Unit

A Domain-specific Language to Facilitate Software Defined Radio Parallel Executable Patterns Deployment on Heterogeneous Architectures

SignalPU: A programming model for DSP applications on parallel and heterogeneous clusters

Risk Estimation Without Using Stein’s Lemma — Application to Image Denoising

Parallel GPU Processing for Fast Radio Signal Propagation Computation in GRASS-RaPlaT

OpenCL Based High-Quality HEVC Motion Estimation on GPU

GPU Declarative Framework

A GPU-based framework for efficient image processing

FPGA: An Efficient And Promising Platform For Real-Time Image Processing Applications

The Implementation of a Real-Time Polyphase Filter

Recent source codes

CuPBoP-AMD: Extending CUDA to AMD Platforms

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

ROCm's implementation of Gromacs

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

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

Most viewed papers (last 30 days)