high performance computing on graphics processing units: hgpu.org

hgpu.org » Algorithms

Parallel probabilistic model checking on general purpose graphics processors

Dragan Bosnacki, Stefan Edelkamp, Damian Sulewski, Anton Wijs

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 285, Probabilistic model checking

October 2, 2011 by hgpu

Parallel Computing based on GPGPU using Compute Unified Device Architecture

Lifeng Xu

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Tags: Algorithms, CUDA, Image processing, nVidia, nVidia GeForce GTX 580, OpenMP, Optimization, Thesis

October 1, 2011 by hgpu

Accelerating Vector Calculations on GPU

Karol Grondzak, Penka Martincova, Ondrej Such

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Tags: Algorithms, Computer science, CUDA, nVidia, Performance, Tesla C1060, Tutorial

October 1, 2011 by hgpu

Large Scale DNA Sequence Alignment and Kernel Method Implemented with GPUs

Songwen Pei, Wenhao Wang, Gang Wei, Baifeng Wu

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Tags: Algorithms, ATI, ATI Radeon HD 4870, Bioinformatics, Biology, Brook, Sequence alignment

October 1, 2011 by hgpu

Interactive Soft Tissue for Surgical Simulation

Gregory S. Ruthenbeck

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Tags: Algorithms, CUDA, Medicine, nVidia, nVidia GeForce GTX 280, Surgical simulation, Thesis, Virtual reality

October 1, 2011 by hgpu

Image registration on GPU

Jeremy Coatelen, Yu Qi

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Tags: Algorithms, ATI, ATI Mobility Radeon HD 5850, Cloud, Image processing, Image registration, nVidia, OpenCL

October 1, 2011 by hgpu

Real-Time Handling of GPU Interrupts in LITMUSRT

Glenn A. Elliott, Chih-Hao Sun, and James H. Anderson

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 470, Operating systems

September 30, 2011 by hgpu

Enhancing Data Locality for Dynamic Simulations through Asynchronous Data Transformations and Adaptive Control

Bo Wu, Eddy Z. Zhang, Xipeng Shen

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Tags: Algorithms, Benchmarking, CMP, Computer science, CUDA, Heterogeneous systems, nVidia, Optimization, Tesla S1070

September 30, 2011 by hgpu

CBench: Analyzing Compute Performance for Modern NVIDIA and AMD GPUs

Varun Sampath

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Source codes

Tags: Algorithms, ATI, ATI Radeon HD 6870, Benchmarking, Computer science, CUDA, nVidia, OpenCL, Package, Tesla C2070

September 30, 2011 by hgpu

Translating GPU binaries to tiered SIMD architectures with Ocelot

Gregory Diamos, Andrew Kerr, Mukil Kesavan

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Tags: Algorithms, Cell processor, Compilers, Computer science, nVidia, PTX

September 30, 2011 by hgpu

Accelerating Geospatial Analysis on GPUs using CUDA

Ying-jie Xia, Li Kuang, Xiu-mei Li

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Tags: Algorithms, CUDA, Earth and Space Sciences, Geoscience, nVidia, nVidia Quadro FX 5600

September 30, 2011 by hgpu

Many-threaded implementation of differential evolution for the CUDA platform

Pavel Kromer, Vaclav Snasel, Jan Platos, Ajith Abraham

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Tags: Algorithms, Benchmarking, Computer science, CUDA, Differential evolution, Genetic programming, nVidia, Optimization, Tesla C2050

September 29, 2011 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

Parallel probabilistic model checking on general purpose graphics processors

Parallel Computing based on GPGPU using Compute Unified Device Architecture

Accelerating Vector Calculations on GPU

Large Scale DNA Sequence Alignment and Kernel Method Implemented with GPUs

Interactive Soft Tissue for Surgical Simulation

Real-Time Handling of GPU Interrupts in LITMUSRT

Enhancing Data Locality for Dynamic Simulations through Asynchronous Data Transformations and Adaptive Control

CBench: Analyzing Compute Performance for Modern NVIDIA and AMD GPUs

Translating GPU binaries to tiered SIMD architectures with Ocelot

Accelerating Geospatial Analysis on GPUs using CUDA

Many-threaded implementation of differential evolution for the CUDA platform

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

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