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Parallel technologies for solving system of the linear equations by the conjugate gradient method

Eduard Bondarenko

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Tags: Computer science, Conjugate gradient solver, CUBLAS, nVidia, OpenACC, OpenMP, Tesla M2070

June 14, 2014 by hgpu

StarPU-MPI: Task Programming over Clusters of Machines Enhanced with Accelerators

Cedric Augonnet, Olivier Aumage, Nathalie Furmento, Samuel Thibault, Raymond Namyst

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Tags: Computer science, CUDA, Heterogeneous systems, MPI, nVidia, OpenCL, Tesla M2070

May 18, 2014 by hgpu

Multi-GPU Implementation of the Minimum Volume Simplex Analysis Algorithm for Hyperspectral Unmixing

Alexander Agathos, Jun Li, Dana Petcu, Antonio Plaza

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Tags: Algorithms, Computer science, CUDA, GPU cluster, nVidia, Sensing, Tesla M2070

April 29, 2014 by hgpu

Task-based FMM for heterogeneous architectures

Emmanuel Agullo, Berenger Bramas, Olivier Coulaud, Eric Darve, Matthias Messner, Toru Takahashi

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Tags: Computer science, CUDA, Fast multipole method, Heterogeneous systems, Numerical simulation, nVidia, Tesla M2070, Tesla M2090

April 9, 2014 by hgpu

Shape Transformation of Multidimensional Density Functions using Distribution Interpolation of the Radon Transforms

Marton Jozsef Toth, Balazs Csebfalvi

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Tags: Algorithms, Computer science, CUDA, nVidia, Radon transform, Tesla M2070

March 17, 2014 by hgpu

Performance Tradeoff Spectrum of Integer and Floating Point Applications Kernels on Various GPUs

M.G.B. Johnson, D. P. Playne, K.A. Hawick

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Tags: Benchmarking, Computer science, CUDA, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 480, nVidia GeForce GTX 580, nVidia GeForce GTX 590, nVidia GeForce GTX 660 M, nVidia GeForce GTX 680, Performance, Tesla M2050, Tesla M2070, Tesla M2075, Tesla M2090

March 6, 2014 by hgpu

A scheduling and runtime framework for a cluster of heterogeneous machines with multiple accelerators

Tarun Beri, Sorav Bansal, Subodh Kumar

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Tags: Computer science, CUDA, FFT, GPU cluster, Heterogeneous systems, Matrix multiplication, Memory model, nVidia, Prefetch, Task scheduling, Tesla M2070

February 11, 2014 by hgpu

Survey on Efficient Linear Solvers for Porous Media Flow Models on Recent Hardware Architectures

Ani Anciaux-Sedrakian, Peter Gottschling, Jean-Marc Gratien, Thomas Guignon

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Tags: Computer science, CUDA, Linear Algebra, nVidia, Review, Tesla M2070, Tesla M2090

February 1, 2014 by hgpu

Taking advantage of hybrid systems for sparse direct solvers via task-based runtimes

Xavier Lacoste, Mathieu Faverge, Pierre Ramet, Samuel Thibault, George Bosilca

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Tags: Algorithms, Computer science, CUDA, Factorization, Heterogeneous systems, nVidia, Sparse direct solvers, Tesla M2070

January 30, 2014 by hgpu

A QUDA-branch to compute disconnected diagrams in GPUs

Constantia Alexandrou, Kyriacos Hadjiyiannakou, Giannis Koutsou, Alexei Strelchenko, Alejandro Vaquero

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Tags: CUDA, GPU cluster, High Energy Physics - Lattice, Monte Carlo simulation, MPI, nVidia, Physics, QCD, Tesla M2070

January 30, 2014 by hgpu

Runtime Support toward Transparent Memory Access in GPU-accelerated Heterogeneous Systems

Feng Ji

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Tags: Computer science, Hadoop, Heterogeneous systems, MapReduce, MPI, nVidia, nVidia GeForce GTX 280, Tesla M2070, Thesis

December 11, 2013 by hgpu

A Highly Extensible Framework for Molecule Dynamic Simulation on GPUs

Xiao Zhang, Wan Guo, Xiao Qin, Xiaonan Zhao

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Source codes

Tags: Chemistry, CUDA, Molecular dynamics, nVidia, Package, Tesla C2070, Tesla M2070, Tesla S1070

December 8, 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

Parallel technologies for solving system of the linear equations by the conjugate gradient method

StarPU-MPI: Task Programming over Clusters of Machines Enhanced with Accelerators

Multi-GPU Implementation of the Minimum Volume Simplex Analysis Algorithm for Hyperspectral Unmixing

Task-based FMM for heterogeneous architectures

Shape Transformation of Multidimensional Density Functions using Distribution Interpolation of the Radon Transforms

Performance Tradeoff Spectrum of Integer and Floating Point Applications Kernels on Various GPUs

A scheduling and runtime framework for a cluster of heterogeneous machines with multiple accelerators

Survey on Efficient Linear Solvers for Porous Media Flow Models on Recent Hardware Architectures

Taking advantage of hybrid systems for sparse direct solvers via task-based runtimes

A QUDA-branch to compute disconnected diagrams in GPUs

Runtime Support toward Transparent Memory Access in GPU-accelerated Heterogeneous Systems

A Highly Extensible Framework for Molecule Dynamic Simulation on GPUs

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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