high performance computing on graphics processing units: hgpu.org

Programming

An Incompressible Navier-Stokes Equations Solver on the GPU Using CUDA

Niklas Karlsson

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Tags: Algorithms, CUDA, Fluid dynamics, Laplace and Poisson equation, Navier-Stokes equations, NSEs, nVidia, nVidia GeForce GTX 660 Ti, Poisson equation, Thesis

October 19, 2013 by hgpu

VDBSCAN+: Performance Optimization Based on GPU Parallelism

Carlos Roberto Valencio, Guilherme Priolli Daniel, Camila Alves de Medeiros, Adriano Mauro Cansian

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Tags: Algorithms, Computer science, CUDA, Data mining, Databases, nVidia, nVidia GeForce GT 525 M

October 18, 2013 by hgpu

Efficient SVM Training Using Parallel Primal-Dual Interior Point Method on GPU

Jing Jin, Xianggao Cai, Xiaola Lin

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Tags: Algorithms, Computer science, CUDA, Factorization, nVidia, Tesla C2050

October 18, 2013 by hgpu

Using CUDA GPU to Accelerate the Ant Colony Optimization Algorithm

Kai-Cheng Wei, Chao-Chin Wu, Chien-Ju Wu

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GT 520

October 18, 2013 by hgpu

Empirical performance modeling of GPU kernels using active learning

Prasanna Balaprakash, Karl Rupp, Azamat Mametjanov, Robert B. Gramacy, Paul D. Hovland, Stefan M. Wild

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Tags: Algorithms, ATI, ATI Radeon HD 7970, Computer science, CUDA, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 470, OpenCL, Performance, Tesla C2050, Tesla K20

October 17, 2013 by hgpu

GPU-acceleration of parallel unconditionally stable group explicit finite difference method

K. Parand, Saeed Zafarvahedian, Sayyed A. Hossayni

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Tags: Algorithms, Computer science, CUDA, Finite difference, Numerical Analysis, nVidia, nVidia GeForce GT 335 M

October 15, 2013 by hgpu

GPU-Specfic Kalman Filtering and Retrodiction for Large-Scale Target Tracking

Sean Tager

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Tags: Algorithms, Computer science, Filtering, Thesis

October 13, 2013 by hgpu

Contributions to parallel stochastic simulation: Application of good software engineering practices to the distribution of pseudorandom streams in hybrid Monte-Carlo simulations

Jonathan Passerat-Palmbach

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Tags: Algorithms, Computer science, CUDA, Java, Monte Carlo simulation, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 590, OpenCL, Pseudo-random number generators, Software Engineering, Stochastic simulation, Tesla C2050, Tesla C2075, Tesla K20, Thesis

October 13, 2013 by hgpu

High performance sequence mining using pairwise statistical significance

Yuhong Zhang, Feng Chen

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Source codes

Tags: Algorithms, Bioinformatics, Biology, CUDA, nVidia, Package, Tesla C2050

October 12, 2013 by hgpu

Regional Heritability Advanced Complex Trait Analysis for GPU and Traditional Parallel Architectures

L. Cebamanos, A. Gray, I. Stewart, A. Tenesa

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Tags: Algorithms, Bioinformatics, Biology, CUDA, nVidia, Tesla K20

October 12, 2013 by hgpu

CUDA-Accelerated ODETLAP: A Parallel Lossy Compression Implementation

Daniel N. Benedetti, W. Randolph Franklin, Wenli Li

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Tags: Algorithms, Compression, CUDA, Differential equations, Image processing, nVidia, Partial differential equations, PDEs, Thrust

October 10, 2013 by hgpu

Scalable Fast Multipole Methods on Heterogeneous Architecture

Q. Hu

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Tags: Algorithms, Computer science, CUDA, Fast multipole method, Heterogeneous systems, N-body simulation, nVidia, nVidia GeForce 8800 GTX, Tesla C1060, Tesla C2050, Thesis

October 9, 2013 by hgpu

CuPBoP-AMD: Extending CUDA to AMD Platforms

CuPBoP: Making CUDA a Portable Language

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

Automated Deep Learning Optimization via DSL-Based Source Code Transformation

ROCm's implementation of Gromacs

GROMACS on AMD GPU-Based HPC Platforms: Using SYCL for Performance and Portability

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

Experiences with implementing Kokkos’ SYCL backend

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Programming

An Incompressible Navier-Stokes Equations Solver on the GPU Using CUDA

VDBSCAN+: Performance Optimization Based on GPU Parallelism

Efficient SVM Training Using Parallel Primal-Dual Interior Point Method on GPU

Using CUDA GPU to Accelerate the Ant Colony Optimization Algorithm

Empirical performance modeling of GPU kernels using active learning

GPU-acceleration of parallel unconditionally stable group explicit finite difference method

GPU-Specfic Kalman Filtering and Retrodiction for Large-Scale Target Tracking

Contributions to parallel stochastic simulation: Application of good software engineering practices to the distribution of pseudorandom streams in hybrid Monte-Carlo simulations

High performance sequence mining using pairwise statistical significance

Regional Heritability Advanced Complex Trait Analysis for GPU and Traditional Parallel Architectures

CUDA-Accelerated ODETLAP: A Parallel Lossy Compression Implementation

Scalable Fast Multipole Methods on Heterogeneous Architecture

Recent source codes

CuPBoP-AMD: Extending CUDA to AMD Platforms

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

ROCm's implementation of Gromacs

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

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

Most viewed papers (last 30 days)