high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications

GPU accelerated simulations of 3D deterministic particle transport using discrete ordinates method

Chunye Gong, Jie Liu, Lihua Chi, Haowei Huang, Jingyue Fang, Zhenghu Gong

Tags: Boltzmann equation, Computational Physics, CUDA, nVidia, Physics, Tesla M2050

April 22, 2011 by hgpu

Pretty Good Accuracy in Matrix Multiplication with GPUs

Matthew Badin, Lubomir Bic, Michael Dillencourt, Alexandru Nicolau

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Tags: Computer science, CUDA, Linear Algebra, Matrix multiplication, nVidia, nVidia GeForce GTX 285

April 21, 2011 by hgpu

Using graphics processors to accelerate the computation of the matrix inverse

P. Ezzatti, E. Quintana-Orti, A. Remon

Source codes

Tags: Computer science, Linear Algebra, Matrix inversion

April 21, 2011 by hgpu

Fast Variable Center-Biased Windowing for High-Speed Stereo on Programmable Graphics Hardware

Jiangbo Lu, G. Lafruit, F. Catthoor

Tags: Image processing, nVidia, nVidia GeForce 7900, Optimization

April 21, 2011 by hgpu

Automatically generating and tuning GPU code for sparse matrix-vector multiplication from a high-level representation

Dominik Grewe, Anton Lokhmotov

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Tags: ATI, ATI Radeon HD 5970, Code generation, Computer science, CUDA, High-level Languages, Linear Algebra, nVidia, OpenCL, Sparse matrix, Tesla S1070

April 21, 2011 by hgpu

Automatically Tuning Sparse Matrix-Vector Multiplication for GPU Architectures

Alexander Monakov, Anton Lokhmotov, Arutyun Avetisyan

Tags: Computer science, Partial differential equations, PDEs, Sparse matrix

April 21, 2011 by hgpu

Assessment of GPU computational enhancement to a 2D flood model

Alfred J. Kalyanapu, Siddharth Shankar, Eric R. Pardyjak, David R. Judi, Steven J. Burian

Tags: CUDA, Earth and Space Sciences, Fluid simulation, nVidia

April 21, 2011 by hgpu

Solving knapsack problems on GPU

V. Boyer, D. El Baz, M. Elkihel

Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 260, Optimization

April 21, 2011 by hgpu

Auto-Tuning CUDA Parameters for Sparse Matrix-Vector Multiplication on GPUs

Ping Guo, Liqiang Wang

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Tags: Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce 9500 GTX, nVidia GeForce GTX 295, Sparse matrix

April 21, 2011 by hgpu

A performance prediction model for the CUDA GPGPU platform

Kishore Kothapalli, Rishabh Mukherjee, M. Suhail Rehman, Suryakant Patidar, P. J. Narayanan, Kannan Srinathan

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Tags: Computer science, CUDA, Matrix multiplication, nVidia, nVidia GeForce GTX 280, Performance

April 21, 2011 by hgpu

Fine-sorting One-dimensional Particle-In-Cell Algorithm with Monte-Carlo Collisions on a Graphics Processing Unit

Philipp Mertmann, Denis Eremin, Thomas Mussenbrock, Ralf Peter Brinkmann, Peter Awakowicz

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Tags: Algorithms, Computational Physics, CUDA, nVidia, nVidia GeForce GTX 480, Particle-in-cell methods, Physics, Plasma physics, Sorting

April 21, 2011 by hgpu

Exploring scalability of FIR filter realizations on Graphics Processing Units

J. Rebacz, E. Oruklu, J. Saniie

Tags: CUDA, Filtering, nVidia, Signal processing

April 20, 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

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high performance computing on graphics processing units: hgpu.org

Applications

GPU accelerated simulations of 3D deterministic particle transport using discrete ordinates method

Pretty Good Accuracy in Matrix Multiplication with GPUs

Using graphics processors to accelerate the computation of the matrix inverse

Fast Variable Center-Biased Windowing for High-Speed Stereo on Programmable Graphics Hardware

Automatically generating and tuning GPU code for sparse matrix-vector multiplication from a high-level representation

Automatically Tuning Sparse Matrix-Vector Multiplication for GPU Architectures

Assessment of GPU computational enhancement to a 2D flood model

Solving knapsack problems on GPU

Auto-Tuning CUDA Parameters for Sparse Matrix-Vector Multiplication on GPUs

A performance prediction model for the CUDA GPGPU platform

Fine-sorting One-dimensional Particle-In-Cell Algorithm with Monte-Carlo Collisions on a Graphics Processing Unit

Exploring scalability of FIR filter realizations on Graphics Processing Units

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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