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Compiling Stream Applications for Heterogeneous Architectures

Amir H. Hormati

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Tags: Compilers, Computer science, CUDA, FPGA, Heterogeneous systems, nVidia, nVidia GeForce GTX 285, Optimization, Tesla C2050, Thesis

October 28, 2011 by hgpu

Architecture-based Performance Evaluation of Genetic Algorithms on Multi/Many-core Systems

Long Zheng, Yanchao Lu, Mengwei Ding, Yao Shen, Minyi Guo, Song Guo

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Tags: Algorithms, Computer science, CUDA, Genetic programming, nVidia, nVidia GeForce GTX 580, Optimization

October 28, 2011 by hgpu

Matrix inversion speed up with CUDA

Jorge Soriano Pinedo

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Tags: Algorithms, Computer science, CUDA, Image reconstruction, Matrix inversion, Matrix multiplication, nVidia, Tesla C1060, Thesis

October 28, 2011 by hgpu

Parallel Random Numbers: As Easy as 1, 2, 3

John K. Salmon, Mark A. Moraes, Ron O. Dror, and David E. Shaw

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Tags: AES, ATI, ATI Radeon HD 6970, Computer science, CUDA, nVidia, nVidia GeForce GTX 580, OpenCL, Package, Performance, Pseudo-random number generators, Security

October 28, 2011 by hgpu

Programming Massively Parallel Processors with CUDA (audio course)

David B. Kirk, Wen-Mei W. Hwu

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Tags: Book, Computer science, CUDA, nVidia, OpenCL, Package, Programming techniques, Review, Tutorial

October 28, 2011 by hgpu

Implementing Domain-Specific Languages for Heterogeneous Parallel Computing

HyoukJoong Lee, Kevin J. Brown, Arvind K. Sujeeth, Hassan Chafi, Kunle Olukotun, Tiark Rompf, Martin Odersky

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Tags: Code generation, Computer science, CUDA, Heterogeneous systems, Machine learning, nVidia, Optimization, Tesla C2050

October 28, 2011 by hgpu

Parallel Computing the Longest Common Subsequence (LCS) on GPUs: Efficiency and Language Suitability

Amine Dhraief, Raik Issaoui, Abdelfettah Belghith

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Tags: Algorithms, Bioinformatics, Biology, CUDA, nVidia, nVidia GeForce GT 430, OpenCL, Sequence alignment

October 28, 2011 by hgpu

The CUDA implementation of the method of lines for the curvature dependent flows

Tomas Oberhuber, Atsushi Suzuki, Vitezslav Zabka

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Tags: Algorithms, CUDA, Differential equations, Finite volume method, Image processing, Mathematics, nVidia, nVidia GeForce GTX 280, ODEs, Ordinary differential equations

October 27, 2011 by hgpu

Off-axis quantitative phase imaging processing using CUDA: toward real-time applications

Hoa Pham, Huafeng Ding, Nahil Sobh, Minh Do, Sanjay Patel, Gabriel Popescu

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Tags: Algorithms, CUDA, Image processing, nVidia, nVidia GeForce GTX 470 M, Real-time graphics, Visualization

October 27, 2011 by hgpu

Parallelization of Single Threaded Applications using OpenMP and CUDA/C

John Burns

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Tags: Computer science, CUDA, Databases, nVidia, OpenMP, Software Engineering

October 27, 2011 by hgpu

Efficient Implementation and Evaluation of Methods for the Estimation of Motion in Image Sequences

Robert Hegner

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 260, Optical flow, Package, Thesis

October 27, 2011 by hgpu

Efficient Implementation of Optical Flow Algorithm Based on Directional Filters on a GPU Using CUDA

Robert Hegner, Ivar Austvoll, Tom Ryen, Guido M. Schuster

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Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 260, Optical flow, Package

October 27, 2011 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

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high performance computing on graphics processing units: hgpu.org

Compiling Stream Applications for Heterogeneous Architectures

Architecture-based Performance Evaluation of Genetic Algorithms on Multi/Many-core Systems

Matrix inversion speed up with CUDA

Parallel Random Numbers: As Easy as 1, 2, 3

Programming Massively Parallel Processors with CUDA (audio course)

Implementing Domain-Specific Languages for Heterogeneous Parallel Computing

Parallel Computing the Longest Common Subsequence (LCS) on GPUs: Efficiency and Language Suitability

The CUDA implementation of the method of lines for the curvature dependent flows

Off-axis quantitative phase imaging processing using CUDA: toward real-time applications

Parallelization of Single Threaded Applications using OpenMP and CUDA/C

Efficient Implementation and Evaluation of Methods for the Estimation of Motion in Image Sequences

Efficient Implementation of Optical Flow Algorithm Based on Directional Filters on a GPU Using CUDA

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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