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Speed and Portability issues for Random Number Generation on Graphical Processing Units with CUDA and other Processing Accelerators

K.A. Hawick, A. Leist, D.P. Playne, M.J. Johnson

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Tags: Cell processor, Computer science, Monte Carlo simulation, nVidia, nVidia GeForce GTX 295, Pseudo-random number generators

February 13, 2011 by hgpu

Automated and parallel code generation for finite-differencing stencils with arbitrary data types

K.A. Hawick and D.P. Playne

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Tags: Code generation, Computer science, CUDA, Finite difference, nVidia, nVidia GeForce GTX 295, Partial differential equations, PDEs

February 13, 2011 by hgpu

Data-Parallelism and GPUs for Lattice Gas Fluid Simulations

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

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Tags: Cellular automata, Computer science, CUDA, Fluid simulation, nVidia, nVidia GeForce GT 220, nVidia GeForce GTX 210, nVidia GeForce GTX 260, nVidia GeForce GTX 295

February 13, 2011 by hgpu

GPU-accelerated indirect boundary element method for voxel model analyses with fast multipole method

Shoji Hamada

Tags: CUDA, Electrodynamics, Fast multipole method, Laplace and Poisson equation, nVidia, nVidia GeForce GTX 295, Physics

February 11, 2011 by hgpu

Fast computing of scattering maps of nanostructures using graphical processing units

Vincent Favre-Nicolin, Johann Coraux, Marie-Ingrid Richard, Hubert Renevier

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Tags: Condensed matter, CUDA, Materials Science, Mesoscale and Nanoscale Physics, nVidia, nVidia GeForce GTX 295, Package, Physics, Python

February 11, 2011 by hgpu

Next-generation acceleration and code optimization for light transport in turbid media using GPUs

Erik Alerstam, William C. Yip Lo, Tianyi D. Han, Jonathan Rose, Stefan Andersson-Engels, Lothar Lilge

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Tags: Biology, CUDA, Monte Carlo simulation, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 295, nVidia GeForce GTX 480, Optics, Package

February 9, 2011 by hgpu

Fast and Scalable CPU/GPU Collision Detection for Rigid and Deformable Surfaces

Simon Pabst, Artur Koch, Wolfgang Strasser

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Tags: Collision detection, Computer science, CUDA, nVidia, nVidia GeForce GTX 295, Physics-based simulation

January 30, 2011 by hgpu

Asynchronous Communication Schemes for Finite Difference Methods on Multiple GPUs

Daniel P. Playne, Kenneth A. Hawick

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Tags: Computer science, CUDA, Finite difference, GPU cluster, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 295

January 30, 2011 by hgpu

EASEA parallelization of tree-based Genetic Programming

Ogier Maitre, S. Querry, Nicolas Lachiche and Pierre Collet

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Tags: Algorithms, Computer science, CUDA, Genetic programming, nVidia, nVidia GeForce GTX 295, Package

January 22, 2011 by hgpu

Speedups between x70 and x120 for a generic local search (memetic) algorithm on a single GPGPU chip

Frederic Kruger, Ogier Maitre, Santiago Jimenez, Laurent Baumes and Pierre Collet

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Tags: Algorithms, Computer science, CUDA, Genetic programming, nVidia, nVidia GeForce GTX 295, Package, Poster

January 21, 2011 by hgpu

Fast Evaluation of GP Trees on GPGPU by Optimizing Hardware Scheduling

Ogier Maitre, Nicolas Lachiche and Pierre Collet

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Tags: Algorithms, Computer science, CUDA, Genetic programming, nVidia, nVidia GeForce GTX 295, Package, Poster

January 21, 2011 by hgpu

Evolving a CUDA kernel from an nVidia template

William B. Langdon, Mark Harman

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Tags: Artificial intelligence, Computer science, CUDA, Genetic programming, nVidia, nVidia GeForce GTX 295

January 21, 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

Speed and Portability issues for Random Number Generation on Graphical Processing Units with CUDA and other Processing Accelerators

Automated and parallel code generation for finite-differencing stencils with arbitrary data types

Data-Parallelism and GPUs for Lattice Gas Fluid Simulations

GPU-accelerated indirect boundary element method for voxel model analyses with fast multipole method

Fast computing of scattering maps of nanostructures using graphical processing units

Next-generation acceleration and code optimization for light transport in turbid media using GPUs

Fast and Scalable CPU/GPU Collision Detection for Rigid and Deformable Surfaces

Asynchronous Communication Schemes for Finite Difference Methods on Multiple GPUs

EASEA parallelization of tree-based Genetic Programming

Speedups between x70 and x120 for a generic local search (memetic) algorithm on a single GPGPU chip

Fast Evaluation of GP Trees on GPGPU by Optimizing Hardware Scheduling

Evolving a CUDA kernel from an nVidia template

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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