high performance computing on graphics processing units: hgpu.org

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Functional Signal Processing with Pure and Faust Using the LLVM Toolkit

Albert Graf

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Tags: Algorithms, Signal processing

September 24, 2011 by hgpu

Improving SIMT Efficiency of Global Rendering Algorithms with Architectural Support for Dynamic Micro-Kernels

Michael Steffen, Joseph Zambreno

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia Quadro FX 5800, Performance, PTX, Rendering

September 23, 2011 by hgpu

Accelerating reaction-diffusion simulations with general-purpose graphics processing units

Matthias Vigelius, Aidan Lane, Bernd Meyer

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Tags: Algorithms, Bioinformatics, Biology, CUDA, nVidia, Package, Rendering, Stochastic simulation

September 23, 2011 by hgpu

Image super-resolution by vectorizing edges

Chia-Jung Hung, Chun-Kai Huang, Bing-Yu Chen

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Tags: Algorithms, Image processing

September 23, 2011 by hgpu

Acceleration of Functional Validation Using GPGPU

Lalith Suresh, Navaneeth Rameshan, M. S. Gaur, Mark Zwolinski, Vijay Laxmi

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Tags: Algorithms, Benchmarking, Computer science, Electronic design automation, nVidia, nVidia Quadro FX 1700, Tesla C870

September 23, 2011 by hgpu

HHT-based time-frequency analysis method for biomedical signal applications

Chin-Feng Lin, Jin-De Zhu

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Tags: Algorithms, Medicine, Signal processing, Wavelet

September 23, 2011 by hgpu

Compact data structure and scalable algorithms for the sparse grid technique

Alin Murarasu, Josef Weidendorfer, Gerrit Buse, Daniel Butnaru, Dirk Pfluger

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Tags: Algorithms, Compression, Computer science, CUDA, Numerical Analysis, nVidia, Optimization, Programming techniques, Tesla C1060

September 23, 2011 by hgpu

Colored stochastic shadow maps

Morgan McGuire, Eric Enderton

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Tags: 3D Graphics and Realism, Algorithms, Computer science, Image generation, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 480, Presentation

September 23, 2011 by hgpu

Unstructured grid applications on GPU: performance analysis and improvement

Lizandro Solano-Quinde, Zhi Jian Wang, Brett Bode, Arun K. Somani

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Tags: Algorithms, Computer science, CUDA, nVidia, Performance, Software Engineering, Tesla T10

September 23, 2011 by hgpu

Orchestration by approximation: mapping stream programs onto multicore architectures

Sardar M. Farhad, Yousun Ko, Bernd Burgstaller, Bernhard Scholz

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Tags: Algorithms, Benchmarking, Compilers, Computer science, Optimization, Performance, Programming Languages

September 23, 2011 by hgpu

Register packing for cyclic reduction: a case study

Andrew Davidson, John D. Owens

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Tags: Algorithms, Computer science, CUDA, Mathematical Software, nVidia, nVidia GeForce GTX 460, Performance

September 22, 2011 by hgpu

On-the-fly elimination of dynamic irregularities for GPU computing

Eddy Z. Zhang, Yunlian Jiang, Ziyu Guo, Kai Tian, Xipeng Shen

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Tags: Algorithms, Compilers, Computer science, CUDA, nVidia, Optimization, Performance, Programming Languages, Tesla C1060

September 22, 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

Functional Signal Processing with Pure and Faust Using the LLVM Toolkit

Improving SIMT Efficiency of Global Rendering Algorithms with Architectural Support for Dynamic Micro-Kernels

Accelerating reaction-diffusion simulations with general-purpose graphics processing units

Image super-resolution by vectorizing edges

Acceleration of Functional Validation Using GPGPU

HHT-based time-frequency analysis method for biomedical signal applications

Compact data structure and scalable algorithms for the sparse grid technique

Colored stochastic shadow maps

Unstructured grid applications on GPU: performance analysis and improvement

Orchestration by approximation: mapping stream programs onto multicore architectures

Register packing for cyclic reduction: a case study

On-the-fly elimination of dynamic irregularities for GPU computing

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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