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Optimization strategies for parallel CPU and GPU implementations of a meshfree particle method

Jose M. Dominguez, Alejandro J.C. Crespo, Moncho Gomez-Gesteira

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Tags: Computational Engineering, Computer science, CUDA, Fluid dynamics, nVidia, nVidia GeForce GTX 480, OpenMP, Optimization, Performance, Tesla C1060

October 18, 2011 by hgpu

Fast N-body Simulations on GPUs

Rio Yokota, Lorena A. Barba

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Tags: Algorithms, Astrophysics, Computer science, CUDA, Fast multipole method, Heterogeneous systems, Mathematical Software, N-body simulation, Numerical Analysis, nVidia, Tesla C2050, Tesla M2050

October 18, 2011 by hgpu

Fast Implementation of DGEMM on Fermi GPU

Guangming Tan, Linchuan Li, Sean Triechle, Everett Phillips, Yungang Bao, Ninghui Sun

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Source codes

Tags: Algorithms, Benchmarking, Computer science, CUBLAS, CUDA, Matrix multiplication, nVidia, Optimization, Performance, Tesla C2050

October 17, 2011 by hgpu

Numerical Accuracy Analysis Based on the Discrete Stochastic Arithmetic on Multiprocessor Platforms

Christian Motzing

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Tags: Computer science, CUDA, Molecular dynamics, Numerical Analysis, nVidia, nVidia GeForce GTX 480, Review, Software Engineering, Thesis

October 17, 2011 by hgpu

Data-Driven Programming Abstractions and Optimization for Multi-Core Platforms

Rebecca L. Collins

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Tags: Algorithms, Cell processor, Computer science, CUDA, nVidia, nVidia GeForce 8800 GTX, Optimization, Programming techniques, Thesis

October 17, 2011 by hgpu

Magneto-hydrodynamics simulation in astrophysics

Bijia Pang

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Tags: Algorithms, Astrophysics, CUDA, Fortran, Heterogeneous systems, Magnetohydrodynamics, nVidia, OpenCL, Physics, Tesla C1060, Tesla C2050, Thesis

October 17, 2011 by hgpu

An Optimization for Fast Generation of Digital Hologram

Joong-Seok Song, Jungsik Park, Sungwoo Kim, Jong-Il Park

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

October 17, 2011 by hgpu

Dynamic Fine-Grain Scheduling of Pipeline Parallelism

Daniel Sanchez, David Lo, Richard M. Yoo, Jeremy Sugerman, Christos Kozyrakis

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Tags: Computer science, CUDA, nVidia, Performance, Programming techniques

October 17, 2011 by hgpu

Programming with Explicit Dependencies. A Framework for Portable Parallel Programming

Eva Burrows

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 9600 GT, nVidia GeForce GTX 250, Programming techniques, Sorting, Thesis

October 17, 2011 by hgpu

A High Performance Parallel Sparse Linear Equation Solver Using CUDA

Andrew J. Martin

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Tags: Algorithms, Computer science, CUDA, Factorization, Linear Algebra, nVidia, nVidia GeForce GTX 570, Thesis

October 17, 2011 by hgpu

Hard-Sphere Collision Simulations with Multiple GPUs, PCIe Extension Buses and GPU-GPU Communications

K.A. Hawick, D.P.Playne

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Tags: Algorithms, CUDA, GPU cluster, Gravitation, nVidia, nVidia GeForce GTX 480, nVidia GeForce GTX 580, Physics, Tesla C2050, Tesla C2070

October 16, 2011 by hgpu

Bit-Packed Damaged Lattice Potts Model Simulations with CUDA and GPUs

Ken A. Hawick, Mitchell G.B. Johnson

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Tags: CUDA, Data parallelism, Ising model, Materials Science, Nearest neighbour, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 295, nVidia GeForce GTX 480, nVidia GeForce GTX 580, Phase transition, Physics, Probability, Tesla C2050, Tesla C2070

October 16, 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

See all packages

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high performance computing on graphics processing units: hgpu.org

Optimization strategies for parallel CPU and GPU implementations of a meshfree particle method

Fast N-body Simulations on GPUs

Fast Implementation of DGEMM on Fermi GPU

Numerical Accuracy Analysis Based on the Discrete Stochastic Arithmetic on Multiprocessor Platforms

Data-Driven Programming Abstractions and Optimization for Multi-Core Platforms

Magneto-hydrodynamics simulation in astrophysics

An Optimization for Fast Generation of Digital Hologram

Dynamic Fine-Grain Scheduling of Pipeline Parallelism

Programming with Explicit Dependencies. A Framework for Portable Parallel Programming

A High Performance Parallel Sparse Linear Equation Solver Using CUDA

Hard-Sphere Collision Simulations with Multiple GPUs, PCIe Extension Buses and GPU-GPU Communications

Bit-Packed Damaged Lattice Potts Model Simulations with CUDA and 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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