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GPU-Mapping: Robotic Map Building with Graphical Multiprocessors

Diego Rodriguez-Losada, Pablo San Segundo, Miguel Hernando, Paloma de la Puente, Alberto Valero

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce 8400 M GS, nVidia GeForce GTX 280

October 29, 2013 by hgpu

Dynamical simulations of extrasolar planetary systems with debris disks using a GPU accelerated N-body code

Alexander Moore

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Tags: Astrophysics, CUDA, N-body simulation, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 285, nVidia GeForce GTX 480, nVidia Quadro FX 5800, Package, Thesis

October 27, 2013 by hgpu

Point to Line Mappings and Other Line Parameterizations not only for Hough Transform

Jiri Havel

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Tags: CUDA, Image processing, nVidia, nVidia GeForce GTX 280, OpenGL, Pattern recognition

October 15, 2013 by hgpu

Power Control for GPU Clusters in processing large-scale streams

Qingkui Chen, Haifeng Wang, Bocheng Liu

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Tags: Computer science, CUDA, Energy-efficient computing, GPU cluster, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480

October 13, 2013 by hgpu

Parallel and Distributed Implementations of Multiple and Two-Dimensional Pattern Matching Algorithms

Charalampos S. Kouzinopoulos

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GT 240, nVidia GeForce GTX 280, String matching, Thesis

October 8, 2013 by hgpu

Improving Resource Utilization in Heterogeneous CPU-GPU Systems

Michael Boyer

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Tags: Algorithms, ATI, ATI Radeon HD 5870, ATI Radeon HD 7970, Biology, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 280, OpenCL, Package, Software Engineering, Thesis

September 23, 2013 by hgpu

Optimization solutions for the segmented sum algorithmic function

Alexandru Pirjan

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Tags: Computer science, CUDA, Memory, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, nVidia GeForce GTX 680, Performance

September 21, 2013 by hgpu

Compilation techniques and language support to facilitate dependence-driven computation

Albert Sidelnik

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Tags: Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Thesis

August 27, 2013 by hgpu

Optimal Control Problem and Power-Efficient Medical Image Processing Using Puma

Himadri Nath Moulick, Moumita Ghosh

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Tags: Algorithms, CUDA, Image processing, Medicine, MRI, nVidia, nVidia GeForce GTX 280, Partial differential equations, PDEs

August 26, 2013 by hgpu

Scalable Dense Linear Algebra on Heterogeneous Hardware

George Bosilca, Aurelien Bouteiller, Anthony Danalis, Thomas Herault, Jakub Kurzak, Piotr Luszczek, Stanimire Tomov, Jack J. Dongarra

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, Linear Algebra, nVidia, nVidia GeForce GTX 280, Tesla C2050

July 30, 2013 by hgpu

OpenCL simulations of two-fluid compressible flows with a random choice method

Philippe Helluy, Jonathan Jung

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Tags: Algorithms, ATI, ATI Radeon HD 5850, ATI Radeon HD 7970, Fluid dynamics, nVidia, nVidia GeForce GT 320 M, nVidia GeForce GTX 280, OpenCL

July 22, 2013 by hgpu

Automatic Generation of FFT Libraries for GPU Platforms

Christos Angelopoulos

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Tags: Algorithms, Computer science, CUDA, FFT, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce GTX 260, nVidia GeForce GTX 280, nVidia GeForce GTX 480, Thesis

July 22, 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_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

See all packages

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high performance computing on graphics processing units: hgpu.org

GPU-Mapping: Robotic Map Building with Graphical Multiprocessors

Dynamical simulations of extrasolar planetary systems with debris disks using a GPU accelerated N-body code

Point to Line Mappings and Other Line Parameterizations not only for Hough Transform

Power Control for GPU Clusters in processing large-scale streams

Parallel and Distributed Implementations of Multiple and Two-Dimensional Pattern Matching Algorithms

Improving Resource Utilization in Heterogeneous CPU-GPU Systems

Optimization solutions for the segmented sum algorithmic function

Compilation techniques and language support to facilitate dependence-driven computation

Optimal Control Problem and Power-Efficient Medical Image Processing Using Puma

Scalable Dense Linear Algebra on Heterogeneous Hardware

OpenCL simulations of two-fluid compressible flows with a random choice method

Automatic Generation of FFT Libraries for GPU Platforms

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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