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The Model of Computation of CUDA and its Formal Semantics

Axel Habermaier

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Tags: Computer science, CUDA, Memory model, nVidia, nVidia GeForce GTX 480, PTX, Thesis

October 25, 2011 by hgpu

The MOSIX Virtual OpenCL (VCL) Cluster Platform

Amnon Barak, Amnon Shiloh

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Source codes

Tags: APU, Computer science, GPU cluster, Heterogeneous systems, MPI, nVidia, nVidia GeForce GTX 480, OpenCL, Operating systems, Package

October 24, 2011 by hgpu

Massively Parallel Algorithms for CFD Simulation and Optimization on Heterogeneous Many-Core Architectures

Austen C. Duffy

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Tags: Algorithms, CUDA, Fluid dynamics, Fortran, GPU cluster, Heterogeneous systems, nVidia, nVidia GeForce GTX 470, nVidia GeForce GTX 480, Optimization, Partial differential equations, PDEs, Thesis

October 23, 2011 by hgpu

On the Usage of GPUs for Efficient Motion Estimation in Medical Image Sequences

Jeyarajan Thiyagalingam, Daniel Goodman, Julia A. Schnabel, Anne Trefethen, Vicente Grau

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Tags: Algorithms, CUDA, Databases, Image processing, Medicine, nVidia, nVidia GeForce GTX 480, Tesla C2070

October 21, 2011 by hgpu

Explicit platform descriptions for heterogeneous many-core architectures

Martin Sandrieser, Siegfried Benkner and Sabri Pllana

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Tags: Code generation, Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 480, OpenCL

October 20, 2011 by hgpu

Radio astronomy beam forming on GPUs

Alessio Sclocco

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Tags: Algorithms, Astrophysics, CUDA, nVidia, nVidia GeForce GTX 480, OpenCL, Thesis

October 18, 2011 by hgpu

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

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

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

Asynchronous Communication for Finite-Difference Simulations on GPU Clusters using CUDA and MPI

D.P. Playne, K.A. Hawick

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Tags: Algorithms, Computer science, CUDA, GPU cluster, MPI, Numerical simulation, nVidia, nVidia GeForce GTX 470, nVidia GeForce GTX 480

October 16, 2011 by hgpu

The Anatomy of High-Performance 2D Similarity Calculations

Imran S. Haque, Vijay S. Pande, W. Patrick Walters

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Tags: Algorithms, Biochemistry, Chemistry, Clustering, CUDA, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 480, Package

October 16, 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

See all packages

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high performance computing on graphics processing units: hgpu.org

The Model of Computation of CUDA and its Formal Semantics

The MOSIX Virtual OpenCL (VCL) Cluster Platform

Massively Parallel Algorithms for CFD Simulation and Optimization on Heterogeneous Many-Core Architectures

On the Usage of GPUs for Efficient Motion Estimation in Medical Image Sequences

Explicit platform descriptions for heterogeneous many-core architectures

Radio astronomy beam forming on GPUs

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

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

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

Asynchronous Communication for Finite-Difference Simulations on GPU Clusters using CUDA and MPI

The Anatomy of High-Performance 2D Similarity Calculations

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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