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Accelerated Dictionary Learning with GPU/Multicore CPU and Its Application to Music Classification

Boyang Gao, Emmanuel Dellandrea, Liming Chen

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Tags: Clustering, CUBLAS, CUDA, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX 285, Signal processing

March 26, 2013 by hgpu

Creating Optimal Code for GPU-Accelerated CT Reconstruction Using Ant Colony Optimization

Eric Papenhausen, Ziyi Zheng, Klaus Mueller

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Tags: Algorithms, Computed tomography, CT, CUDA, Image processing, Image reconstruction, nVidia, nVidia GeForce GTX 480, Optimization

March 26, 2013 by hgpu

A Region Growing Segmentation Algorithm for GPUs

Patrick Nigri Happ, Raul Queiroz Feitosa, Cristiana Bentes, Ricardo Farias

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Tags: Algorithms, CUDA, Image processing, nVidia, nVidia GeForce 9600 GT, nVidia GeForce GTX 480

March 26, 2013 by hgpu

Hyperspectral Unmixing on GPUs and Multi-Core Processors: A Comparison

Sergio Bernabe, Sergio Sanchez, Antonio Plaza, Sebastian Lopez, Jon Atli Benediktsson, Roberto Sarmiento

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Tags: Algorithms, CUBLAS, CUDA, Image processing, nVidia, nVidia GeForce GTX 580, Tesla C1060

March 26, 2013 by hgpu

Recurrence quantification analysis in images with CUDA

Thiago de Lima Prado

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Tags: Algorithms, CUDA, Image processing, nVidia, nVidia GeForce GTX 460

March 24, 2013 by hgpu

Real-Time Implementation of the Pixel Purity Index Algorithm for Endmember Identification on GPUs

Xianyun Wu, Bormin Huang, Antonio Plaza, Yunsong Li, Chengke Wu

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Tags: Algorithms, Computational Complexity, Heterogeneous systems, Image processing, nVidia, nVidia GeForce GTX 590, Tesla C1060

March 23, 2013 by hgpu

Performance study of filtered back-projection algorithms implemented on GPUs

Bruno Faria

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Tags: Computed tomography, CT, CUDA, Image processing, Medicine, nVidia, nVidia GeForce GTX 580, Performance, Tomography

March 21, 2013 by hgpu

Automated and interactive approaches for optimal surface finding based segmentation of medical image data

Shanhui Sun

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Tags: CUDA, Image processing, Medicine, nVidia, Tesla C1060, Thesis, Ultrasound, Visualization

March 14, 2013 by hgpu

Parallel Particle Swarm Optimization for Image Segmentation

Agustinus Kristiadi, Pranowo Pranowo, Paulus Mudjihartono

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Tags: Clustering, CUDA, Image processing, nVidia, nVidia GeForce G 110 M, Particle swarm optimization

March 14, 2013 by hgpu

CPU and/or GPU: Revisiting the GPU Vs. CPU Myth

Kishore Kothapalli, Dip Sankar Banerjee, P. J. Narayanan, Surinder Sood, Aman Kumar Bahl, Shashank Sharma, Shrenik Lad, Krishna Kumar Singh, Kiran Matam, Sivaramakrishna Bharadwaj, Rohit Nigam, Parikshit Sakurikar, Aditya Deshpande, Ishan Misra, Siddharth Choudhary, Shubham Gupta

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Tags: Computer science, Databases, Hybrid computing, Image processing, nVidia, nVidia GeForce GT 520, Sparse matrix, Tesla T10

March 14, 2013 by hgpu

Signal Processing and General Purpose Computing on GPU

Muge Guher

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Tags: CUDA, nVidia, Signal processing, Tesla C2050

March 9, 2013 by hgpu

Efficient Detection of Sunspots with GPU Acceleration Through CUDA

Kenny May

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Tags: Astrophysics, CUDA, Image processing, nVidia, nVidia GeForce GT 430, nVidia GeForce GTX 470, Tesla C2050

March 2, 2013 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 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

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

Parallel Gaussian process with kernel approximation in CUDA

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