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Towards fast and certified multiple-precision libraries

Valentina Popescu

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Tags: Algorithms, Computer science, CUDA, Extended precision, nVidia, Tesla C2075, Thesis

July 26, 2014 by hgpu

Parallel Computations for Hierarchical Agglomerative Clustering using CUDA

S.A. Arul Shalom, Manoranjan Dash

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Tags: Algorithms, Clustering, Computer science, CUDA, Data mining, nVidia, nVidia GeForce 8800 GTS

July 26, 2014 by hgpu

Parallel solutions of static Hamilton-Jacobi equations for simulations of geological folds

Tor Gillberg, Are Magnus Bruaset, Oyvind Hjelle, Mohammed Sourouri

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Tags: Algorithms, CUDA, Mathematics, nVidia, OpenMP, Tesla K20

July 26, 2014 by hgpu

Multi-Core Programming Design Patterns: Stream Processing Algorithms for Dynamic Scene Perceptions

Kannappan Palaniappan

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Tags: Algorithms, Benchmarking, Cell processor, Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 460, Tesla C2070

July 24, 2014 by hgpu

Abstraction and Implementation of Unstructured Grid Algorithms on Massively Parallel Heterogeneous Architectures

Istvan Zoltan Reguly

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Tags: Algorithms, Code generation, Computer science, CUDA, Differential equations, FEM, Finite element method, Finite volume method, Fluid dynamics, Heterogeneous systems, Linear Algebra, nVidia, Partial differential equations, PDEs, Programming techniques, Tesla C2070, Tesla K20, Tesla K40, Thesis

July 24, 2014 by hgpu

Electromagnetic Computation and Visualization of Transmission Particle Model and its Simulation Based on GPU

Yingnian Wu, Lin Zhang, Lan Mu

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Tags: Algorithms, CUDA, Electrodynamics, FDTD, nVidia, Raytracing, Visualization

July 24, 2014 by hgpu

Parallel kinetic Monte Carlo simulation of Coulomb glasses

Ezequiel E. Ferrero, Alejandro B. Kolton, Matteo Palassini

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Source codes

Tags: Algorithms, Condensed matter, CUDA, Disordered Systems and Neural Networks, Monte Carlo simulation, nVidia, nVidia GeForce GTX 470, Package, Tesla C2075, Tesla K20

July 24, 2014 by hgpu

Solution Level Parallelization of Local Search Metaheuristic Algorithm on GPU

S. V. Ghorpade, S. M. Kamalapur

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Tags: Algorithms, Computer science, CUDA, Data parallelism, Metaheuristics, nVidia, nVidia GeForce GTX 680, Search

July 23, 2014 by hgpu

Automated Long-Term Monitoring of Parallel Microfluidic Operations Applying a Machine Vision-Assisted Positioning Method

Hon Ming Yip, John C. S. Li, Kai Xie, Xin Cui, Agrim Prasad, Qiannan Gao, Chi Chiu Leung, Raymond H. W. Lam

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Tags: Algorithms, Computer vision, CUDA, Image processing, nVidia, nVidia GeForce GT 640

July 22, 2014 by hgpu

Parallel Computing: Accelerating Computational Science and Engineering (CSE)

M. Bader, A. Bode, H.-J. Bungartz

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Tags: Algorithms, Book, Computer science, CUDA, Heterogeneous systems, nVidia

July 22, 2014 by hgpu

High Performance Low Power Embedded Vision Systems

Antonis S. Nikitakis

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Tags: Algorithms, ARM, Computer science, Computer vision, CUDA, FPGA, nVidia, nVidia GeForce GTX 285, nVidia GeForce GTX 580, OpenCV, Thesis

July 22, 2014 by hgpu

Data Parallel Quadtree Indexing and Spatial Query Processing of Complex Polygon Data on GPUs

Jianting Zhang, Simin You, Le Gruenwald

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Tags: Algorithms, Computer science, CUDA, Data parallelism, Databases, nVidia, nVidia GeForce GTX Titan

July 20, 2014 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

Programming

Towards fast and certified multiple-precision libraries

Parallel Computations for Hierarchical Agglomerative Clustering using CUDA

Parallel solutions of static Hamilton-Jacobi equations for simulations of geological folds

Multi-Core Programming Design Patterns: Stream Processing Algorithms for Dynamic Scene Perceptions

Abstraction and Implementation of Unstructured Grid Algorithms on Massively Parallel Heterogeneous Architectures

Electromagnetic Computation and Visualization of Transmission Particle Model and its Simulation Based on GPU

Parallel kinetic Monte Carlo simulation of Coulomb glasses

Solution Level Parallelization of Local Search Metaheuristic Algorithm on GPU

Automated Long-Term Monitoring of Parallel Microfluidic Operations Applying a Machine Vision-Assisted Positioning Method

Parallel Computing: Accelerating Computational Science and Engineering (CSE)

High Performance Low Power Embedded Vision Systems

Data Parallel Quadtree Indexing and Spatial Query Processing of Complex Polygon Data on GPUs

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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