high performance computing on graphics processing units: hgpu.org

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PATUS: A Code Generation and Auto-Tuning Framework For Parallel Stencil Computations

Matthias Christen, Olaf Schenk, Helmar Burkhart

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Tags: Code generation, Computer science, CUDA, nVidia, Optimization, Package, Tesla C2050

November 8, 2011 by hgpu

Speculative Parallel Evaluation Of Classification Trees On GPGPU Compute Engines

Jason Spencer

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia Quadro FX 2000, Optimization, Pattern recognition

November 8, 2011 by hgpu

MELT-a Translated Domain Specific Language Embedded in the GCC Compiler

Basile Starynkevitch

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Tags: Compilers, Computer science, OpenCL, Optimization, Programming Languages, Software Engineering

November 7, 2011 by hgpu

Functional Programming for High-Performance Computing on Heterogeneous Architectures

Sylvain Henry

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia Quadro FX 5800, OpenCL, Optimization, Performance, Programming Languages, Programming techniques

November 7, 2011 by hgpu

Fast TV-L1 Optical Flow for Interactivity

Emmanuel d'Angelo, Johan Paratte, Gilles Puy, Pierre Vandergheynst

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Tags: Algorithms, Computer science, Computer vision, nVidia, nVidia GeForce GTX 320 M, OpenCL, Optical flow, Optimization, Package

November 7, 2011 by hgpu

GPU-accelerated Convex Multi-phase Image Segmentation

Subrahmanyam Gorthi, Arnaud Le Carvennec, Hadrien Copponnex, Xavier Bresson, Jean-Philippe Thiran

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Tags: Algorithms, Computational Complexity, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 285, Optimization, Package

November 7, 2011 by hgpu

Advanced MRI reconstruction toolbox with accelerating on GPU

Xiao-Long Wu, Yue Zhuo, Fan Lam, Maojing Fu, Justin P. Haldar, Wen-Mei Hwu, Zhi-Pei Liang, Bradley P. Sutton, Jiading Gai

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Tags: Algorithms, CUDA, FFT, Image reconstruction, Magnetic resonance imaging, MRI, nVidia, nVidia GeForce GTX 280, Optimization, Physics

November 6, 2011 by hgpu

Challenges for compiler support for exascale computing

Daniel Quinlan

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Tags: Compilers, Computer science, CUDA, nVidia, Optimization, Presentation

November 5, 2011 by hgpu

Computing Optimal Cycle Mean in Parallel on CUDA

Jiri Barnat, Petr Bauch, Lubos Brim, Milan Ceska

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Tags: Algorithms, Computer science, CUDA, Data Structures and Algorithms, nVidia, nVidia GeForce GTX 480, Optimization

November 4, 2011 by hgpu

Topology Optimization with Unstructured Meshes on Graphics Processing Units (GPUs)

Tomas Zegard Latrach

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Tags: Algorithms, Benchmarking, Computer science, CUDA, nVidia, Optimization, Tesla T10, Thesis

November 3, 2011 by hgpu

An Implementation of Differential Evolution for Independent Tasks Scheduling on GPU

Pavel Kromer, Jan Platos, Vaclav Snasel, Ajith Abraham

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Tags: Algorithms, Artificial intelligence, Computer science, CUDA, Differential evolution, Heterogeneous systems, nVidia, Optimization, Task scheduling, Tesla C2050

November 1, 2011 by hgpu

Optimal Control of the Process Systems Using Graphic Processing Unit

Arash Sadrieh, Parisa A. Bahri

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

October 31, 2011 by hgpu

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

Experiences with implementing Kokkos’ SYCL backend

ROCm's implementation of Gromacs

GROMACS on AMD GPU-Based HPC Platforms: Using SYCL for Performance and Portability

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

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high performance computing on graphics processing units: hgpu.org

PATUS: A Code Generation and Auto-Tuning Framework For Parallel Stencil Computations

Speculative Parallel Evaluation Of Classification Trees On GPGPU Compute Engines

MELT-a Translated Domain Specific Language Embedded in the GCC Compiler

Functional Programming for High-Performance Computing on Heterogeneous Architectures

Fast TV-L1 Optical Flow for Interactivity

GPU-accelerated Convex Multi-phase Image Segmentation

Advanced MRI reconstruction toolbox with accelerating on GPU

Challenges for compiler support for exascale computing

Computing Optimal Cycle Mean in Parallel on CUDA

Topology Optimization with Unstructured Meshes on Graphics Processing Units (GPUs)

An Implementation of Differential Evolution for Independent Tasks Scheduling on GPU

Optimal Control of the Process Systems Using Graphic Processing Unit

Recent source codes

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

ROCm's implementation of Gromacs

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

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