high performance computing on graphics processing units: hgpu.org

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Power, Energy and Speed of Embedded and Server Multi-Cores applied to Distributed Simulation of Spiking Neural Networks: ARM in NVIDIA Tegra vs Intel Xeon quad-cores

Pier Stanislao Paolucci, Roberto Ammendola, Andrea Biagioni, Ottorino Frezza, Francesca Lo Cicero, Alessandro Lonardo, Michele Martinelli, Elena Pastorelli, Francesco Simula, Piero Vicini

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Tags: ARM, Computer science, MPI, Neural networks, Neurons and Cognition, nVidia, STDP

May 15, 2015 by hgpu

Real-Time Phase Masks for Interactive Stimulation of Optogenetic Neurons

Stephan C. Kramer, Johannes Hagemann, D. Russell Luke

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Tags: Biology, CUDA, Mathematics, Neurons and Cognition, nVidia, Optimization, Tesla C2070

February 5, 2013 by hgpu

Making Human Connectome Faster: GPU Acceleration of Brain Network Analysis

Di Wu, Tianji Wu, Yi Shan, Yu Wang, Yong He, Ningyi Xu, Huazhong Yang

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Tags: ATI, ATI IL, ATI Radeon HD 5870, ATI Stream, Medicine, Neurons and Cognition, Neuroscience

April 26, 2011 by hgpu

Fast recursive filters for simulating nonlinear dynamic systems

J. H. van Hateren

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Tags: Algorithms, Biology, Neurons and Cognition

November 13, 2010 by hgpu

A Markovian event-based framework for stochastic spiking neural networks

Jonathan Touboul, Olivier Faugeras

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Tags: Algorithms, Mathematics, Neural networks, Neurons and Cognition, Statistics, Statistics Theory

November 13, 2010 by hgpu

A framework for simulating and estimating the state and functional topology of complex dynamic geometric networks

Marius Buibas, Gabriel A. Silva

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Tags: Biological Physics, Condensed matter, CUDA, Disordered Systems and Neural Networks, Mathematical Physics, Neurons and Cognition, nVidia, Package, Physics, Tesla C1060

November 9, 2010 by hgpu

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

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

Optical flow algorithms for SYCL

SYCL in the edge: performance and energy evaluation for heterogeneous acceleration

OpenMP5-Offload-OpenMC-Intel-PVC

Distributed OpenMP Offloading of OpenMC on Intel GPU MAX Accelerators

See all packages

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high performance computing on graphics processing units: hgpu.org

Power, Energy and Speed of Embedded and Server Multi-Cores applied to Distributed Simulation of Spiking Neural Networks: ARM in NVIDIA Tegra vs Intel Xeon quad-cores

Real-Time Phase Masks for Interactive Stimulation of Optogenetic Neurons

Making Human Connectome Faster: GPU Acceleration of Brain Network Analysis

Fast recursive filters for simulating nonlinear dynamic systems

A Markovian event-based framework for stochastic spiking neural networks

A framework for simulating and estimating the state and functional topology of complex dynamic geometric networks

Recent source codes

QArray

Celerity: High-level C++ for Accelerator Clusters

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

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

Optical flow algorithms for SYCL

OpenMP5-Offload-OpenMC-Intel-PVC

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