high performance computing on graphics processing units: hgpu.org

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A comparison of CPUs, GPUs, FPGAs, and massively parallel processor arrays for random number generation

David Barrie Thomas, Lee Howes, Wayne Luk

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Tags: Algorithms, Computer science, CUDA, FPGA, nVidia, nVidia GeForce GTX 280, Pseudo-random number generators

March 20, 2011 by hgpu

Mersenne Twister Random Number Generation on FPGA, CPU and GPU

Xiang Tian, Khaled Benkrid

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Tags: Algorithms, Computer science, CUDA, FPGA, nVidia, nVidia GeForce 8800 GTX, Pseudo-random number generators

March 20, 2011 by hgpu

Performance Evaluation of the NVIDIA GeForce 8800 GTX GPU for Machine Learning

A El Zein, E McCreath, Alistair Rendell, Alex Smola

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Tags: Computer science, CUDA, Machine learning, nVidia, nVidia GeForce 8800 GTX, Presentation, Sparse matrix

March 20, 2011 by hgpu

Solving Large Regression Problems using an Ensemble of GPU-accelerated ELMs

Mark Van Heeswijk, Yoan Miche, Erkki Oja, Amaury Lendasse

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Tags: Computer science, CUDA, CULA, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 295, Tesla C1060

March 20, 2011 by hgpu

Joint Forces: From Multithreaded Programming to GPU Computing

Frank Feinbube, Peter Troger, Andreas Polze

Tags: Computer science, Optimization, Performance

March 20, 2011 by hgpu

Mean Shift Parallel Tracking on GPU

Peihua Li, Lijuan Xiao

Tags: Algorithms, Computer science, Computer vision, CUDA, nVidia, Video tracking

March 19, 2011 by hgpu

Method for simulation of coastal terrain on GPU

Jun Chen, Peng Sheng, Zhen He

Tags: 3D Graphics and Realism, Computer science, Rendering

March 19, 2011 by hgpu

Exploring utilisation of GPU for database applications

Slawomir Walkowiak, Konrad Wawruch, Marita Nowotka, Lukasz Ligowski, Witold Rudnicki

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Tags: Computer science, CUDA, Databases, nVidia, Tesla S1070

March 19, 2011 by hgpu

Efficient and Quality Contouring Algorithms on the GPU

L. Schmitz, L. F. Scheidegger, D. K. Osmari, C. A. Dietrich, J. L. D. Comba

Tags: Algorithms, Computer science, Image generation

March 19, 2011 by hgpu

Implementing a GPU Programming Model on a non-GPU Accelerator Architecture

Stephen M. Kofsky, Daniel R. Johnson, John A. Stratton, Wen-Mei W. Hwu, Sanjay J. Patel, Steven S. Lumetta

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Tags: Computer science, CUDA, nVidia, Optimization, Programming techniques, Tesla T10

March 19, 2011 by hgpu

Scalable Multi Agent Simulation on the GPU

Avi Bleiweiss

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Tags: Artificial intelligence, Computer science, CUDA, nVidia, Presentation

March 19, 2011 by hgpu

Password Recovery for RAR Files Using CUDA

Guang Hu, Jianhua Ma, Benxiong Huang

Tags: AES, Archivers, Computer science, CUDA, nVidia, Security

March 19, 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

Applications

A comparison of CPUs, GPUs, FPGAs, and massively parallel processor arrays for random number generation

Mersenne Twister Random Number Generation on FPGA, CPU and GPU

Performance Evaluation of the NVIDIA GeForce 8800 GTX GPU for Machine Learning

Solving Large Regression Problems using an Ensemble of GPU-accelerated ELMs

Joint Forces: From Multithreaded Programming to GPU Computing

Mean Shift Parallel Tracking on GPU

Method for simulation of coastal terrain on GPU

Exploring utilisation of GPU for database applications

Efficient and Quality Contouring Algorithms on the GPU

Implementing a GPU Programming Model on a non-GPU Accelerator Architecture

Scalable Multi Agent Simulation on the GPU

Password Recovery for RAR Files Using CUDA

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

Most viewed papers (last 30 days)