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Kernel Specialization for Improved Adaptability and Performance on Graphics Processing Units (GPUs)

Nicholas John Moore

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Tags: Computer science, CUDA, FPGA, Image reconstruction, nVidia, Optimization, Tesis, Tesla C1060, Tesla C2070

October 26, 2012 by hgpu

The impact of GPU/Multicore in Signal Processing: a quantitative approach

V.M Garcia, A.Gonzalez, C. Gonzalez, F.J. Martinez-Zaldivar, C.Ramiro, S. Roger, A.M. Vidal

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Tags: CUDA, CULA, nVidia, nVidia Quadro FX 5800, Signal processing, Tesla C2070

October 20, 2012 by hgpu

Scalable GPU Acceleration of B-Spline Signal Processing Operations

Alexander Karantza

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Tags: CUDA, nVidia, Signal processing, Tesla C2070, Thesis

October 13, 2012 by hgpu

Fast Parallel Implementation of Fractional Packing and Covering Linear Programs

Slobodan Jelic, Soren Laue, Domagoj Matijevic, Patrick Wijerama

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Tags: Algorithms, CUDA, Mathematics, nVidia, Tesla C2070

October 13, 2012 by hgpu

CUTE solutions for two-point correlation functions from large cosmological datasets

David Alonso

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Source codes

Tags: Astrophysics, CUDA, Instrumentation and Methods for Astrophysics, nVidia, nVidia Quadro NVS 4200 M, Package, Tesla C2070

October 8, 2012 by hgpu

Performance Analysis of an Ultrasound Reconstruction Algorithm for Non Destructive Testing

Antoine Pedron, Lionel Lacassagne, Victor Barbillon, Franck Bimbard, Gilles Rougeron, Stephane Le Berre

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 580, OpenCL, Tesla C1060, Tesla C2070, Ultrasound

October 3, 2012 by hgpu

Improved Row-Grouped CSR Format for Storing of Sparse Matrices on GPU

Tomas Oberhuber, Martin Heller

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Tags: Computer science, CUDA, nVidia, Optimization, Sparse matrix, Tesla C2070

September 26, 2012 by hgpu

A Parallel Auxiliary Grid AMG Method for GPU

Lu Wang, Xiaozhe Hu, Jonathan Cohen, Jinchao Xu

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Tags: Algorithms, Computer science, CUDA, Numerical Analysis, nVidia, Tesla C2070

September 26, 2012 by hgpu

Some examples of instant computations of fluid dynamics on GPU

Florian De Vuyst, Christophe Labourdette

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Tags: CUDA, Fluid dynamics, Lattice Boltzmann model, Navier-Stokes equations, NSEs, nVidia, Tesla C2070, Visualization

September 21, 2012 by hgpu

On the Validation and Applications of a Parallel Flexible Multi-Body Dynamics Implementation

Daniel J. Melanz

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Tesla C2070, Thesis

September 14, 2012 by hgpu

Systematic Approach in Optimizing Numerical Memory-Bound Kernels on GPU

Ahmad Abdelfattah, David Keyes, Hatem Ltaief

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Tags: Algorithms, Computer science, CUBLAS, CUDA, Linear Algebra, nVidia, Tesla C2070

September 13, 2012 by hgpu

Performance Improvement of TOUGH2 Simulation with Graphics Processing Unit

Yusuke Shimotoku, Toshiaki Tanaka, Ryuichi Itoi

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Tags: Computer science, CUDA, nVidia, Performance, Tesla C2070

September 10, 2012 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

Kernel Specialization for Improved Adaptability and Performance on Graphics Processing Units (GPUs)

The impact of GPU/Multicore in Signal Processing: a quantitative approach

Scalable GPU Acceleration of B-Spline Signal Processing Operations

Fast Parallel Implementation of Fractional Packing and Covering Linear Programs

CUTE solutions for two-point correlation functions from large cosmological datasets

Performance Analysis of an Ultrasound Reconstruction Algorithm for Non Destructive Testing

Improved Row-Grouped CSR Format for Storing of Sparse Matrices on GPU

A Parallel Auxiliary Grid AMG Method for GPU

Some examples of instant computations of fluid dynamics on GPU

On the Validation and Applications of a Parallel Flexible Multi-Body Dynamics Implementation

Systematic Approach in Optimizing Numerical Memory-Bound Kernels on GPU

Performance Improvement of TOUGH2 Simulation with Graphics Processing Unit

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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