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GPU accelerated atmospheric chemical kinetics in the ECHAM/MESSy (EMAC) Earth system model

Michail Alvanos, Theodoros Christoudias

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Tags: Chemistry, Code generation, CUDA, Earth and Space Sciences, Fortran, nVidia, Package, Tesla M2070

May 2, 2017 by hgpu

Sparse Matrix-Vector Multiplication on GPGPUs

Salvatore Filippone, Valeria Cardellini, Davide Barbieri, Alessandro Fanfarillo

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Tags: Computer science, CUDA, Fortran, nVidia, nVidia GeForce GTX 660, Package, Review, Sparse matrix, Tesla K20, Tesla K40, Tesla M2070

April 3, 2017 by hgpu

UNICORN: A Bulk Synchronous Programming Model, Framework and Runtime for Hybrid CPU-GPU Clusters

Tarun Beri

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Tags: Computer science, CUDA, FFT, GPU cluster, Linear Algebra, Matrix multiplication, nVidia, Package, Prefetch, Tesla M2070, Thesis

November 5, 2016 by hgpu

Reordering strategy for blocking optimization in sparse linear solvers

Gregoire Pichon, Mathieu Faverge, Pierre Ramet, Jean Roman

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Tags: Algorithms, Computer science, CUDA, Factorization, Linear Algebra, nVidia, Sparse direct solvers, Tesla M2070

October 15, 2016 by hgpu

A survey of sparse matrix-vector multiplication performance on large matrices

Max Grossman, Christopher Thiele, Mauricio Araya-Polo, Florian Frank, Faruk O. Alpak, Vivek Sarkar

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Tags: Computer science, CUDA, Linear Algebra, Numerical Analysis, nVidia, Performance, Sparse matrix, survey, Tesla M2070

August 4, 2016 by hgpu

A Data Parallel Algorithm for Seismic Raytracing

Allen D. Malony, Stephanie McCumsey, Joseph Byrnes, Craig Rasmusen, Soren Rasmusen, Erik Keever, Doug Toomey

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Tags: Algorithms, Earth and Space Sciences, Geoscience, nVidia, OpenCL, OpenMP, Raytracing, Seismology, Tesla K80, Tesla M2070

July 26, 2016 by hgpu

On the design of sparse hybrid linear solvers for modern parallel architectures

Stojce Nakov

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, Linear Algebra, MPI, nVidia, Sparse linear iterative solvers, Sparse matrix, Tesla K40, Tesla M2070, Thesis

April 29, 2016 by hgpu

A Reproducible Research Methodology for Designing and Conducting Faithful Simulations of Dynamic HPC Applications

Luka Stanisic

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Tags: Computer science, CUDA, Heterogeneous systems, Linear Algebra, nVidia, nVidia Quadro FX 5800, Tesla C2050, Tesla K20, Tesla K40, Tesla M2070, Tesla M2075, Thesis

February 1, 2016 by hgpu

Parallel FDTD Arithmetic Simulation Based on Distributed Heterogeneous Cluster System

Feng Yuan, Tang Xiaobin, Gong Xiaoyan

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Tags: Computer science, Electrodynamics, FDTD, Finite-difference time-domain, GPU cluster, Heterogeneous systems, MPI, nVidia, OpenCL, Physics, Tesla K20, Tesla M2070

December 22, 2015 by hgpu

Accelerating Applications with Pattern-specific Optimizations on Accelerators and Coprocessors

Linchuan Chen

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Tags: Computer science, CUDA, Heterogeneous systems, MapReduce, Matrix multiplication, MPI, nVidia, Sparse matrix, Task scheduling, Tesla M2070, Thesis

October 13, 2015 by hgpu

A GPU-based Parallel Ant Colony Algorithm for Scientific Workflow Scheduling

Pengfei Wang, Huifang Li, Baihai Zhang

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Tags: Algorithms, Ant colony optimization, Computer science, CUDA, nVidia, Tesla M2070

September 15, 2015 by hgpu

Three storage formats for sparse matrices on GPGPUs

Davide Barbieri, Valeria Cardellini, Alessandro Fanfarillo, Salvatore Filippone

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Tags: Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 660, Package, Sparse matrix, Tesla M2070

September 9, 2015 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

GPU accelerated atmospheric chemical kinetics in the ECHAM/MESSy (EMAC) Earth system model

Sparse Matrix-Vector Multiplication on GPGPUs

UNICORN: A Bulk Synchronous Programming Model, Framework and Runtime for Hybrid CPU-GPU Clusters

Reordering strategy for blocking optimization in sparse linear solvers

A survey of sparse matrix-vector multiplication performance on large matrices

A Data Parallel Algorithm for Seismic Raytracing

On the design of sparse hybrid linear solvers for modern parallel architectures

A Reproducible Research Methodology for Designing and Conducting Faithful Simulations of Dynamic HPC Applications

Parallel FDTD Arithmetic Simulation Based on Distributed Heterogeneous Cluster System

Accelerating Applications with Pattern-specific Optimizations on Accelerators and Coprocessors

A GPU-based Parallel Ant Colony Algorithm for Scientific Workflow Scheduling

Three storage formats for sparse matrices on GPGPUs

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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