high performance computing on graphics processing units: hgpu.org

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Scalable, High Performance Fourier Domain Optical Coherence Tomography: Why FPGAs and Not GPGPUs

Jian Li, Marinko V. Sarunic, Lesley Shannon

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Tags: Algorithms, CUDA, Data acquisition, FPGA, Medicine, nVidia, nVidia GeForce GTX 295, nVidia GeForce GTX 480, Tomography

September 21, 2011 by hgpu

Texture-based visualization of uncertainty in flow fields

Ralf P. Botchen, Daniel Weiskopf, Thomas Ertl

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Tags: Computer science, Data acquisition, DirectX, Filtering, HLSL, Image generation, nVidia, nVidia GeForce 6800 GT, Visualization

August 5, 2011 by hgpu

Exploiting Graphic Processing Units Parallelism to Improve Intelligent Data Acquisition System Performance in JET’s Correlation Reflectometer

J. Nieto, G. de Arcas, J. Vega, M. Ruiz, J. M. Lopez, E. Barrera, A. Murari, A. Fonseca

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Tags: CUDA, Data acquisition, nVidia, Physics, Tesla C1060

June 30, 2011 by hgpu

GPUs for fast triggering and pattern matching at the CERN experiment NA62

Gianluca Lamanna, Gianmaria Collazuol, Marco Sozzi

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Tags: CUDA, Data acquisition, High Energy Physics - Experiment, Nuclear Experiment, nVidia, Pattern recognition, Physics, Tesla C1060

June 20, 2011 by hgpu

A trigger system based on Graphics Processing Unit (GPU)

G. Collazuol, G. Lamanna, M. Sozzi

Tags: Data acquisition, High Energy Physics - Experiment, Physics

May 21, 2011 by hgpu

GPUs for fast pattern matching in the RICH of the NA62 experiment

Gianluca Lamanna, Gianmaria Collazuol, Marco Sozzi

Tags: Data acquisition, Pattern recognition, Physics

November 20, 2010 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

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high performance computing on graphics processing units: hgpu.org

Scalable, High Performance Fourier Domain Optical Coherence Tomography: Why FPGAs and Not GPGPUs

Texture-based visualization of uncertainty in flow fields

Exploiting Graphic Processing Units Parallelism to Improve Intelligent Data Acquisition System Performance in JET’s Correlation Reflectometer

GPUs for fast triggering and pattern matching at the CERN experiment NA62

A trigger system based on Graphics Processing Unit (GPU)

GPUs for fast pattern matching in the RICH of the NA62 experiment

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)