high performance computing on graphics processing units: hgpu.org

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Leveraging Parallelism with CUDA and OpenCL

S. Park, D. Shires, J. Ross, D. Richie

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Tags: AMD FireStream 9250, ATI, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce 8800 GTX, OpenCL, Programming techniques, Tesla C1060

December 18, 2011 by hgpu

Efficient Computational Methods for Uncertainty Quantification of Large Systems

Gaurav Gaurav

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Tags: Computer science, CUDA, Nonlinear analysis, nVidia, Tesla C1060, Thesis

December 18, 2011 by hgpu

Real-Time Implementation of a Full Hyperspectral Unmixing Chain on Graphics Processing Units

Sergio Sanchez, Antonio Plaza

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Tags: Algorithms, CUDA, Image processing, nVidia, Tesla C1060

December 18, 2011 by hgpu

Parallel paradigms in optimal structural design

Van Huyssteen, Salomon Stephanus

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 280, OpenCL, Optimization, Thesis

December 18, 2011 by hgpu

Massively Parallel Logic Simulation with GPUs

Yuhao Zhu, Bo Wang, Yangdong Deng

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Tags: Algorithms, Computer science, CUDA, Electronic design automation, nVidia, nVidia GeForce GTX 280, Optimization, Performance

December 17, 2011 by hgpu

Extendable pattern-oriented optimization directives

Huimin Cui, Jingling Xue, Lei Wang, Yang Yang, Xiaobing Feng, Dongrui Fan

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Tags: Algorithms, Code generation, Computer science, CUDA, nVidia, nVidia GeForce GTX 285, Optimization

December 17, 2011 by hgpu

Quartile and Outlier Detection on Heterogeneous Clusters Using Distributed Radix Sort

Kyle L. Spafford, Jeremy S. Meredith, Jeffrey S. Vetter

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, Package, Sorting, Tesla M2070

December 17, 2011 by hgpu

Parallel Mining of Neuronal Spike Streams on Graphics Processing Units

Yong Cao, Debprakash Patnaik, Sean Ponce, Jeremy Archuleta, Patrick Butler, Wu-chun Feng, Naren Ramakrishnan

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Tags: Algorithms, Computer science, CUDA, Data mining, Neuroscience, nVidia, nVidia GeForce GTX 280

December 17, 2011 by hgpu

GPU implementation of JPEG2000 for hyperspectral image compression

Milosz Ciznicki, Krzysztof Kurowski, Antonio Plaza

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Tags: Algorithms, Compression, CUDA, Image processing, JPEG2000, nVidia, nVidia GeForce GTX 480

December 17, 2011 by hgpu

Code Optimization Techniques for Graphics Processing Units

Fernando Magno Quintao Pereira

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Tags: Algorithms, Book, Code generation, Computer science, CUDA, nVidia, nVidia GeForce 9400 M, Optimization, Package, Programming techniques, PTX, Tutorial

December 17, 2011 by hgpu

Customizable Memory Schemes for Data Parallel Accelerators

Chunyang Gou

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Tags: Computer science, CUDA, Memory model, nVidia, nVidia GeForce GTX 280, Performance, Programming techniques, Thesis

December 17, 2011 by hgpu

Parallel mesh adaptation and graph analysis using graphics processing units

Timothy P. McGuiness

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Tags: Algorithms, CUDA, FEM, Finite element method, Fluid dynamics, Graph theory, MPI, nVidia, nVidia GeForce GTX 295, Tesla S1070

December 17, 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

Leveraging Parallelism with CUDA and OpenCL

Efficient Computational Methods for Uncertainty Quantification of Large Systems

Real-Time Implementation of a Full Hyperspectral Unmixing Chain on Graphics Processing Units

Parallel paradigms in optimal structural design

Massively Parallel Logic Simulation with GPUs

Extendable pattern-oriented optimization directives

Quartile and Outlier Detection on Heterogeneous Clusters Using Distributed Radix Sort

Parallel Mining of Neuronal Spike Streams on Graphics Processing Units

GPU implementation of JPEG2000 for hyperspectral image compression

Code Optimization Techniques for Graphics Processing Units

Customizable Memory Schemes for Data Parallel Accelerators

Parallel mesh adaptation and graph analysis using graphics processing units

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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