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Speeding up the MATLAB Hyperspectral Image Analysis Toolbox using GPUs and the Jacket Toolbox

S. Rosario-Torres, M. Velez-Reyes

Tags: Algorithms, Image processing

June 14, 2011 by hgpu

Parallel implementation of artificial neural network training

S. Scanzio, S. Cumani, R. Gemello, F. Mana, P. Laface

Tags: Acoustics, CUDA, Neural networks, nVidia, Signal processing, Speech recognition

June 14, 2011 by hgpu

CuParcone A High-Performance Evolvable Neural Network Model

Xiaoxi Chen, Lin Gao, Hugo de Garis

Tags: CUDA, Image processing, Image recognition, Neural networks, nVidia

June 14, 2011 by hgpu

Handwritten Digit Recognition with a Committee of Deep Neural Nets on GPUs

Dan C. Ciresan, Ueli Meier, Luca M. Gambardella, Jurgen Schmidhuber

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Tags: Artificial intelligence, Computer vision, Image processing, Image recognition, Neural networks, nVidia, nVidia GeForce GTX 480

June 10, 2011 by hgpu

Parallel rate-distortion optimized intra mode decision on multi-core graphics processors using greedy-based encoding orders

Ngai-Man Cheung, Oscar C. Au, Man-Cheung Kung, Xiaopeng Fan

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Tags: Cg, Compression, H.264/AVC, Image processing, nVidia, nVidia GeForce 8800 GTS, OpenGL, Video decoding

June 8, 2011 by hgpu

Tuning Manifold Harmonics Filters

Thomas Lewiner, Thales Vieira, Alex Bordignon, Allyson Cabral, Clarissa Marques, Joao Paixao, Lis Custodio, Marcos Lage, Maria Andrade, Renata Nascimento, Scarlett de Botton, Sinesio Pesco, Helio Lopes, Vinicius Mello, Adelailson Peixoto, Dimas Martinez

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Tags: Computer science, GLSL, Image generation, nVidia, nVidia GeForce GT 130, OpenGL, Real-time graphics, Rendering, Signal processing, Visualization

June 7, 2011 by hgpu

A new parallel video understanding and retrieval system

Ke-yan Liu, Tong Zhang, Lei Wang

Tags: Image processing, Image recognition, MapReduce, nVidia, nVidia Quadro FX 4600

June 7, 2011 by hgpu

Fast Hardware-Accelerated Volume Rendering of CT Scans

Ronghua Liang, Zhigeng Pan, M. Krokos, Mao Chen, Jiarui Bao, Cheng Li

Tags: Computed tomography, CT, Image processing, Medicine, Rendering

June 6, 2011 by hgpu

Scene image classfying via the Partially Connected Neural Network

Li-lan Pan, Yue Zhang

Tags: Image processing, Image registration, Neural networks

June 6, 2011 by hgpu

An adaptive octree textures painting algorithm

Gang Dang, Hang Li, Zhi-Quan Cheng, Kai Xu, Yan-Zhen Wang, Bao Li

Tags: 3D Graphics and Realism, Algorithms, Image generation, Image processing

June 6, 2011 by hgpu

Accelerating biomedical signal processing algorithms with parallel programming on graphic processor units

Evdokimos I. Konstantinidis, Christos A. Frantzidis, Lazaros Tzimkas, Costas Pappas, Panagiotis D. Bamidis

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Tags: CUDA, Medicine, nVidia, nVidia GeForce 8600 GT, nVidia GeForce 9600 GT, nVidia GeForce GTS 250, Signal processing

June 6, 2011 by hgpu

Employ Bump Mapping to Enrich the 3D NPR Image

Zhien Luo

Tags: 3D Graphics and Realism, Image processing, Rendering

June 5, 2011 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 plugin for PySCF

Python-Based Quantum Chemistry Calculations with GPU Acceleration

QArray

QArray: a GPU-accelerated constant capacitance model simulator for large quantum dot arrays

Celerity: High-level C++ for Accelerator Clusters

Balancing Tracking Granularity and Parallelism in Many-Task Systems: The Horizons Approach

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

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