high performance computing on graphics processing units: hgpu.org

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Exploring Fine-Grained Task-based Execution on Multi-GPU Systems

Long Chen, Oreste Villa, Guang R. Gao

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Tags: Computer science, CUDA, GPU cluster, Molecular dynamics, nVidia, Tesla C1060

November 1, 2011 by hgpu

Using DRBL to Deploy MPICH2 and CUDA on Green Computing

Wu Jiun-Yu, Wang Yao-Tsung, Shiau Steven, Wang Hui Ching

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Tags: Computer science, CUDA, Energy-efficient computing, Green, nVidia, nVidia GeForce 9800 GT

November 1, 2011 by hgpu

Quantum chemical many-body theory on heterogeneous nodes

A. Eugene DePrince, Jeff R. Hammond

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Tags: Algorithms, Computational chemistry, CUBLAS, CUDA, Heterogeneous systems, nVidia, Presentation, Tesla C1060, Tesla C2050

November 1, 2011 by hgpu

An Implementation of Differential Evolution for Independent Tasks Scheduling on GPU

Pavel Kromer, Jan Platos, Vaclav Snasel, Ajith Abraham

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Tags: Algorithms, Artificial intelligence, Computer science, CUDA, Differential evolution, Heterogeneous systems, nVidia, Optimization, Task scheduling, Tesla C2050

November 1, 2011 by hgpu

Fast computation of scattering maps of nanostructures using graphical processing units

Vincent Favre-Nicolin, Johann Coraux, Marie-Ingrid Richard, Hubert Renevier

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Tags: Condensed matter, CUDA, Materials Science, Mesoscale and Nanoscale Physics, nVidia, nVidia GeForce GTX 295, Package, Python

November 1, 2011 by hgpu

Extremely large scale simulation of a Kardar-Parisi-Zhang model using graphics cards

Jefrrey Kelling, Geza Odor

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Tags: Algorithms, Computational Physics, Condensed matter, CUDA, Finite size scaling, nVidia, Physics

November 1, 2011 by hgpu

Parallel Smoothers for Matrix-based Multigrid Methods on Unstructured Meshes Using Multicore CPUs and GPUs

Vincent Heuveline, Dimitar Lukarski, Nico Trost, Jan-Philipp Weiss

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Tags: Algorithms, Computer science, CUDA, Differential equations, Linear Algebra, nVidia, Package, Partial differential equations, PDEs, Tesla S1070

October 31, 2011 by hgpu

Optimal Control of the Process Systems Using Graphic Processing Unit

Arash Sadrieh, Parisa A. Bahri

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Optimization, Performance

October 31, 2011 by hgpu

SIMD Re-Convergence At Thread Frontiers

Gregory Diamos, Andrew Kerr, Haicheng Wu, Sudhakar Yalamanchili, Benjamin Ashbaugh, Subramaniam Maiyuran

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Tags: Computer science, CUDA, nVidia, Performance, Programming Languages, PTX

October 31, 2011 by hgpu

Rapid Performance of a Generalized Distance Calculation

Scott Fisackerly, Eric Chu, David L. Foster

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Tags: Algorithms, Clustering, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Tesla C1060

October 31, 2011 by hgpu

Low Latency Complex Event Processing on Parallel Hardware

Gianpaolo Cugola, Alessandro Margara

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Tags: Algorithms, Computer science, CUDA, Filtering, nVidia, nVidia GeForce GTX 460

October 31, 2011 by hgpu

Fast Speaker Diarization Using a High-Level Scripting Language

Ekaterina Gonina, Gerald Friedland, Henry Cook, Kurt Keutzer

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Tags: Clustering, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Python, Speech recognition

October 31, 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

Exploring Fine-Grained Task-based Execution on Multi-GPU Systems

Using DRBL to Deploy MPICH2 and CUDA on Green Computing

Quantum chemical many-body theory on heterogeneous nodes

An Implementation of Differential Evolution for Independent Tasks Scheduling on GPU

Fast computation of scattering maps of nanostructures using graphical processing units

Extremely large scale simulation of a Kardar-Parisi-Zhang model using graphics cards

Parallel Smoothers for Matrix-based Multigrid Methods on Unstructured Meshes Using Multicore CPUs and GPUs

Optimal Control of the Process Systems Using Graphic Processing Unit

SIMD Re-Convergence At Thread Frontiers

Rapid Performance of a Generalized Distance Calculation

Low Latency Complex Event Processing on Parallel Hardware

Fast Speaker Diarization Using a High-Level Scripting Language

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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