high performance computing on graphics processing units: hgpu.org

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Real-time intraoperative full-range complex FD-OCT guided cerebral blood vessel identification and brain tumor resection in neurosurgery

Kang Zhang, Yong Huang, Gustavo Pradilla, Betty Tyler, Jin U. Kang

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Tags: CUDA, Medicine, Neuroscience, nVidia, nVidia GeForce GTX 480, Tomography, Visualization

December 10, 2011 by hgpu

Fast and Robust Pyramid-based Image Processing

Sylvain Paris, Samuel W. Hasinoff, Jan Kautz, Mathieu Aubry, Fredo Durand

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Tags: Algorithms, Filtering, Image processing, nVidia, nVidia GeForce GTX 480

December 10, 2011 by hgpu

Real-time dual-mode standard/complex Fourier-domain OCT system using graphics processing unit accelerated 4D signal processing and visualization

Kang Zhang, Jin U. Kang

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Tags: CUDA, FFT, Medicine, nVidia, nVidia GeForce GTX 480, Rendering, Signal processing, Tomography, Visualization

December 10, 2011 by hgpu

Speeding up the evaluation phase of GP classification algorithms on GPUs

Alberto Cano, Amelia Zafra, Sebastian Ventura

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Source codes

Tags: Algorithms, Computer science, CUDA, Genetic programming, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, Package

December 8, 2011 by hgpu

Evolving Neural Networks on GPUs

Johannes Hofmann

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Tags: Algorithms, Computer science, CUDA, Evolutionary Computations, Finance, Neural and Evolutionary Computing, Neural networks, nVidia, nVidia GeForce GTX 480, Tesla C1060

December 7, 2011 by hgpu

An Efficient Parallel Motion Estimation Algorithm and X264 Parallelization in CUDA

Youngsub Ko, Youngmin Yi, Soonhoi Ha

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Tags: Algorithms, CUDA, Data parallelism, H.264/AVC, Image processing, nVidia, nVidia GeForce GTX 480

December 7, 2011 by hgpu

Sparse-Matrix-CG-Solver in CUDA

Dominik Michels

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Tags: Algorithms, Computer science, Conjugate gradient solver, CUDA, nVidia, nVidia GeForce GTX 480, Sparse matrix

December 7, 2011 by hgpu

Accelerating Braided B+ Tree Searches on a GPU with CUDA

Jordan Fix, Andrew Wilkes, Kevin Skadron

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Tags: Algorithms, Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 480

December 7, 2011 by hgpu

Effective Mapping of Grammatical Evolution to CUDA Hardware Model

Petr Pospichal

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Tags: Algorithms, Computer science, CUDA, Evolutionary Computations, nVidia, nVidia GeForce GTX 480, Performance

December 7, 2011 by hgpu

Automatic Fusions of CUDA-GPU Kernels for Parallel Map

Jan Fousek, Jiri Filipovic, Matus Madzin

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Optimization, Performance

December 6, 2011 by hgpu

Multiprocessing Acceleration of H.264/AVC Motion Estimation Full Search Algorithm under CUDA Architecture

Eduarda R. Monteiro, Bruno B. Vizzotto, Claudio M. Diniz, Bruno Zatt, Sergio Bampi

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Tags: Algorithms, CUDA, H.264/AVC, Image processing, nVidia, nVidia GeForce GTX 480

December 6, 2011 by hgpu

DTAM: Dense tracking and mapping in real-time

Richard A. Newcombe, Steven J. Lovegrove, Andrew J. Davison

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Tags: Algorithms, Computer science, Computer vision, Image alignment, nVidia, nVidia GeForce GTX 480

December 6, 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_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

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high performance computing on graphics processing units: hgpu.org

Real-time intraoperative full-range complex FD-OCT guided cerebral blood vessel identification and brain tumor resection in neurosurgery

Fast and Robust Pyramid-based Image Processing

Real-time dual-mode standard/complex Fourier-domain OCT system using graphics processing unit accelerated 4D signal processing and visualization

Speeding up the evaluation phase of GP classification algorithms on GPUs

Evolving Neural Networks on GPUs

An Efficient Parallel Motion Estimation Algorithm and X264 Parallelization in CUDA

Sparse-Matrix-CG-Solver in CUDA

Accelerating Braided B+ Tree Searches on a GPU with CUDA

Effective Mapping of Grammatical Evolution to CUDA Hardware Model

Automatic Fusions of CUDA-GPU Kernels for Parallel Map

Multiprocessing Acceleration of H.264/AVC Motion Estimation Full Search Algorithm under CUDA Architecture

DTAM: Dense tracking and mapping in real-time

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)