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A framework for parallel unstructured grid applications on GPUs

Mike Giles

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Tags: Code generation, Computer science, CUDA, GPU cluster, MPI, nVidia, OpenCL, OpenMP, Package, PDEs, Presentation

June 5, 2011 by hgpu

QR Factorization on a Multicore Node Enhanced with Multiple GPU Accelerators

Emmanuel Agullo, Cedric Augonnet, Jack Dongarra, Mathieu Faverge, Hatem Ltaief, Samuel Thibault, Stanimire Tomov

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Tags: Computer science, CUDA, Factorization, GPU cluster, Linear Algebra, nVidia, nVidia Quadro FX 5800, Tesla S1070

June 5, 2011 by hgpu

Accelerating GPU kernels for dense linear algebra

Rajib Nath, Stanimire Tomov, Jack Dongarra

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Tags: BLAS, Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 280

June 4, 2011 by hgpu

A Scalable High Performant Cholesky Factorization for Multicore with GPU Accelerators

Hatem Ltaief, Stanimire Tomov, Rajib Nath, Peng Du and Jack Dongarra

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Tags: Computer science, CUDA, Factorization, Linear Algebra, nVidia, Tesla S1070

June 4, 2011 by hgpu

Synthesizing Subdivision Meshes Using Real Time Tessellation

Matthias Hollander, Tamy Boubekeur

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Tags: 3D Graphics and Realism, Computer science, nVidia, nVidia GeForce GTX 295, OpenGL, Tessellation, Triangular meshes, Visualization

June 3, 2011 by hgpu

High Performance Stereo Vision Designed for Massively Data Parallel Platforms

Wei Yu, Tsuhan Chen, Franz Franchetti, James C. Hoe

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Tags: Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, Real-time graphics, Stereo vision

June 3, 2011 by hgpu

Interactive Approximate Rendering of Reflections, Refractions, and Caustics

Wei Hu, Kaihuai Qin

Tags: Computer science, Raytracing, Rendering

June 3, 2011 by hgpu

Mixed-Tool Performance Analysis on Hybrid Multicore Architectures

Peng Du, Piotr Luszczek, Stanimire Tomov, Jack Dongarra

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Tags: BLAS, Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 280, Performance

June 3, 2011 by hgpu

CUDA-based Signed Distance Field Calculation for Adaptive Grids

Taejung Park, Sung-Ho Lee, Jong-Hyun Kim, Chang-Hun Kim

Tags: Algorithms, Computer science, CUDA, nVidia, Triangular meshes

June 2, 2011 by hgpu

Sparse matrix computations on manycore GPU’s

Michael Garland

Tags: Algorithms, Computer science, CUDA, nVidia, Path problems, Programming techniques, Sparse matrix

June 2, 2011 by hgpu

MapCG: writing parallel program portable between CPU and GPU

Chuntao Hong, Dehao Chen, Wenguang Chen, Weimin Zheng, Haibo Lin

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Tags: Computer science, CUDA, High-level Languages, MapReduce, nVidia, nVidia GeForce GTX 280, Programming techniques

June 2, 2011 by hgpu

Swarm’s flight: Accelerating the particles using C-CUDA

Lucas de P. Veronese, Renato A. Krohling

Tags: Algorithms, Benchmarking, Computer science, CUDA, nVidia, Optimization

June 2, 2011 by hgpu

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

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

Optical flow algorithms for SYCL

SYCL in the edge: performance and energy evaluation for heterogeneous acceleration

OpenMP5-Offload-OpenMC-Intel-PVC

Distributed OpenMP Offloading of OpenMC on Intel GPU MAX Accelerators

See all packages

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high performance computing on graphics processing units: hgpu.org

A framework for parallel unstructured grid applications on GPUs

QR Factorization on a Multicore Node Enhanced with Multiple GPU Accelerators

Accelerating GPU kernels for dense linear algebra

A Scalable High Performant Cholesky Factorization for Multicore with GPU Accelerators

Synthesizing Subdivision Meshes Using Real Time Tessellation

High Performance Stereo Vision Designed for Massively Data Parallel Platforms

Interactive Approximate Rendering of Reflections, Refractions, and Caustics

Mixed-Tool Performance Analysis on Hybrid Multicore Architectures

CUDA-based Signed Distance Field Calculation for Adaptive Grids

Sparse matrix computations on manycore GPU’s

MapCG: writing parallel program portable between CPU and GPU

Swarm’s flight: Accelerating the particles using C-CUDA

Recent source codes

QArray

Celerity: High-level C++ for Accelerator Clusters

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

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

Optical flow algorithms for SYCL

OpenMP5-Offload-OpenMC-Intel-PVC

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