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Accelerating glassy dynamics using graphics processing units

Peter H. Colberg, Felix Hofling

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Tags: Computational Physics, CUDA, nVidia, nVidia GeForce GTX 280, Package, Physics, Soft Condensed Matter

November 8, 2010 by hgpu

Multifactor dimensionality reduction for graphics processing units enables genome-wide testing of epistasis in sporadic ALS

Casey S. Greene, Nicholas A. Sinnott-Armstrong, Daniel S. Himmelstein, Paul J. Park, Jason H. Moore, Brent T. Harris

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Tags: Bioinformatics, Biology, CUDA, Genetics, nVidia, nVidia GeForce GTX 295, Package

November 7, 2010 by hgpu

Parallel hyperbolic PDE simulation on clusters: Cell versus GPU

Scott Rostrup, Hans De Sterck

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Tags: Cell processor, CUDA, Hyperbolic PDEs, Hyperbolic system, Mathematics, nVidia, Package, Tesla C2050, Tesla T10

November 7, 2010 by hgpu

Biomolecular electrostatics simulation with a parallel FMM-based BEM, using up to 512 GPUs

Rio Yokota, Jaydeep P. Bardhan, Matthew G. Knepley, L. A. Barba, Tsuyoshi Hamada

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Tags: Chemistry, CUDA, GPU cluster, Molecular modeling, nVidia, nVidia GeForce GTX 295, Package

November 7, 2010 by hgpu

MDLab: A molecular dynamics simulation prototyping environment

Trevor Cickovski, Santanu Chatterjee, Jacob Wenger, Christopher R. Sweet, Jesus A. Izaguirre

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Tags: Chemistry, Computational chemistry, CUDA, Molecular dynamics, nVidia, Package, Python

November 6, 2010 by hgpu

CUDASW++ 2.0: enhanced Smith-Waterman protein database search on CUDA-enabled GPUs based on SIMT and virtualized SIMD abstractions

Yongchao Liu, Bertil Schmidt, Douglas Maskell

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Tags: Bioinformatics, Biology, Computational biology, CUDA, nVidia, nVidia GeForce GTX 280, nVidia GeForce GTX 295, Package, Smith-Waterman algorithm

November 6, 2010 by hgpu

Automatic fitting of spiking neuron models to electrophysiological recordings

Cyrille Rossant, Dan F. Goodman, Jonathan Platkiewicz, Romain Brette

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Tags: Adaptive threshold, Biology, CUDA, Distributed computing, Neuroscience, nVidia, nVidia GeForce GTX 295, Optimization, Package

November 6, 2010 by hgpu

StoreGPU: exploiting graphics processing units to accelerate distributed storage systems

Samer Al-Kiswany, Abdullah Gharaibeh, Elizeu Santos-Neto, George Yuan, Matei Ripeanu

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Tags: Computer science, CUDA, Hashing, nVidia, nVidia GeForce 8600 GTS, nVidia GeForce 9800 GTX, Package, Storage system

November 6, 2010 by hgpu

Accelerating Dust Temperature Calculations with Graphics Processing Units

Patrik Jonsson, Joel Primack

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Tags: Astrophysics, CUDA, Instrumentation and Methods for Astrophysics, nVidia, Package, Physics, Tesla C1060

November 6, 2010 by hgpu

SAPPORO: A way to turn your graphics cards into a GRAPE-6

Evghenii Gaburov, Stefan Harfst, Simon P. Zwart

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Tags: Astrophysics, CUDA, Instrumentation and Methods for Astrophysics, nVidia, nVidia GeForce 9800 GX2, Package, Physics

November 6, 2010 by hgpu

GPU’s for event reconstruction in the FairRoot framework

M. {Al-Turany}, F. {Uhlig}, R. {Karabowicz}

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Tags: CUDA, Instrumentation and measurement, Nuclear physics, nVidia, Package, Particle physics and field theory, Physics, Tesla C1060

November 5, 2010 by hgpu

RenderAnts: Interactive REYES Rendering on GPUs

Kun Zhou, Qiming Hou, Zhong Ren, Minmin Gong, Xin Sun, Baining Guo

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Tags: Computer science, Image generation, nVidia, nVidia GeForce GTX 280, Package, Raytracing, Rendering, Shaders

November 5, 2010 by hgpu

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

Experiences with implementing Kokkos’ SYCL backend

ROCm's implementation of Gromacs

GROMACS on AMD GPU-Based HPC Platforms: Using SYCL for Performance and Portability

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

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high performance computing on graphics processing units: hgpu.org

Accelerating glassy dynamics using graphics processing units

Multifactor dimensionality reduction for graphics processing units enables genome-wide testing of epistasis in sporadic ALS

Parallel hyperbolic PDE simulation on clusters: Cell versus GPU

Biomolecular electrostatics simulation with a parallel FMM-based BEM, using up to 512 GPUs

MDLab: A molecular dynamics simulation prototyping environment

CUDASW++ 2.0: enhanced Smith-Waterman protein database search on CUDA-enabled GPUs based on SIMT and virtualized SIMD abstractions

Automatic fitting of spiking neuron models to electrophysiological recordings

StoreGPU: exploiting graphics processing units to accelerate distributed storage systems

Accelerating Dust Temperature Calculations with Graphics Processing Units

SAPPORO: A way to turn your graphics cards into a GRAPE-6

GPU’s for event reconstruction in the FairRoot framework

RenderAnts: Interactive REYES Rendering on GPUs

Recent source codes

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

ROCm's implementation of Gromacs

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

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