high performance computing on graphics processing units: hgpu.org

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3D Recursive Gaussian IIR on GPU and FPGAs: A Case Study for Accelerating Bandwidth-Bounded Applications

Jason Cong, Muhuan Huang, Yi Zou

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Tags: CUDA, FPGA, Image processing, nVidia, Optimization, Tesla C1060

December 19, 2011 by hgpu

An Efficient Simulation Environment for Modeling Large-Scale Cortical Processing

Micah Richert, Jayram Moorkanikara Nageswaran, Nikil Dutt, Jeffrey L. Krichmar

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Source codes

Tags: Biology, CUDA, Neural networks, Neuroscience, nVidia, Package, Tesla C1060

December 19, 2011 by hgpu

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

A Comparative Analysis of GPU Implementations of Spectral Unmixing Algorithms

Sergio Sanchez, Antonio Plaza

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Tags: Algorithms, CUDA, Image processing, nVidia, nVidia GeForce GTX 275, Tesla C1060

December 17, 2011 by hgpu

Efficient XML Path Filtering Using GPUs

Roger Moussalli, Robert Halstead, Mariam Salloum, Walid Najjar, Vassilis J. Tsotras

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Tags: Computer science, CUDA, Data Structures and Algorithms, FPGA, nVidia, Optimization, Tesla C1060

December 16, 2011 by hgpu

GPU Algorithms for the Estimation of Environmental Models Based on Large Datasets

Francesco Finazzi, Michela Cameletti

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Tags: Algorithms, CUDA, Earth and Space Sciences, Factorization, nVidia, Tesla C1060

December 15, 2011 by hgpu

Free surface flow simulations on GPGPUs using the LBM

Christian Janssen, Manfred Krafczy

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Tags: Algorithms, CUDA, Fluid dynamics, Lattice Boltzmann model, nVidia, nVidia GeForce GTX 275, Tesla C1060

December 15, 2011 by hgpu

Power consumption of mixed precision in the iterative solution of sparse linear systems

Hartwig Anzt, Vincent Heuveline, Bjorn Rocker, Maribel Castillo, Juan C. Fernandez, Rafael Mayo, Enrique S. Quintana-Orti

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Tags: Algorithms, Computer science, CUDA, Energy-efficient computing, Mixed precision, nVidia, Tesla C1060

December 14, 2011 by hgpu

Lattice Boltzmann Simulation of Binary Mixture Diffusion Using Modern Graphics Processors

Mohammad Amin Safi, Mahmud Ashrafizaadeh, Amir Ali Ashrafizaadeh

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Tags: CUDA, Fluid dynamics, Lattice Boltzmann model, nVidia, Optimization, Tesla C1060

December 13, 2011 by hgpu

Parallelization of an Ultrasound Reconstruction Algorithm for non Destructive Testing on Multicore CPU and GPU

Antoine Pedron, Lionel Lacassagne, Franck Bimbard, Stephane Le Berre

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Tags: Algorithms, CUDA, nVidia, Optimization, Physics, Tesla C1060, Tesla C2070, Ultrasound

December 12, 2011 by hgpu

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

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

See all packages

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high performance computing on graphics processing units: hgpu.org

3D Recursive Gaussian IIR on GPU and FPGAs: A Case Study for Accelerating Bandwidth-Bounded Applications

An Efficient Simulation Environment for Modeling Large-Scale Cortical Processing

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

A Comparative Analysis of GPU Implementations of Spectral Unmixing Algorithms

Efficient XML Path Filtering Using GPUs

GPU Algorithms for the Estimation of Environmental Models Based on Large Datasets

Free surface flow simulations on GPGPUs using the LBM

Power consumption of mixed precision in the iterative solution of sparse linear systems

Lattice Boltzmann Simulation of Binary Mixture Diffusion Using Modern Graphics Processors

Parallelization of an Ultrasound Reconstruction Algorithm for non Destructive Testing on Multicore CPU and GPU

Recent source codes

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

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

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