high performance computing on graphics processing units: hgpu.org

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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

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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

PROM: an open-source software framework to enhance the robustness and performance of predictive models against such changes during deployment

Enhancing Deployment-Time Predictive Model Robustness for Code Analysis and Optimization

DeepSpeed: a deep learning optimization library that makes distributed training and inference easy, efficient, and effective

Scalable Access-Pattern Aware I/O Acceleration and Multi-Tiered Data Management for HPC and AI Workloads

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

SW#SYCL

Analyzing the Performance Portability of SYCL across CPUs, GPUs, and Hybrid Systems with Protein Database Search

tdg-benchs: benchmarks used to test the performance of taskgraph

Leveraging the potential of task-based programming with OpenMP task graphs

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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

PROM: an open-source software framework to enhance the robustness and performance of predictive models against such changes during deployment

DeepSpeed: a deep learning optimization library that makes distributed training and inference easy, efficient, and effective

HPX: a C++ Standard Library for Concurrency and Parallelism

TorchQC: Quantum Dynamics and Machine Learning

Matrix multiplication using Tensor Cores in CUDA

CPP Joules: Energy Measurement tool for CPP/CUDA programs

HPC-Coder-v2

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

SW#SYCL

tdg-benchs: benchmarks used to test the performance of taskgraph

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