high performance computing on graphics processing units: hgpu.org

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Vivaldi: A Domain-Specific Language for Volume Processing and Visualization on Distributed Heterogeneous Systems

Hyungsuk Choi, Woohyuk Choi, Tran Minh Quan, David G. C. Hildebrand, Hanspeter Pfister, Senior Member, Won-Ki Jeong

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Tags: CUDA, GPU cluster, Heterogeneous systems, Image processing, nVidia, Python, Rendering, Tesla M2090, Visualization

August 9, 2014 by hgpu

Infiniband-Verbs on GPU: A case study of controlling an Infiniband network device from the GPU

Lena Oden, Holger Froning, Franz-Joseph Pfreundt

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Tags: Computer science, CUDA, GPU cluster, Heterogeneous systems, Networks, nVidia, Tesla K20

July 14, 2014 by hgpu

A Hybrid Parallel Implementation of the Aho-Corasick and Wu-Manber Algorithms Using NVIDIA CUDA and MPI Evaluated on a Biological Sequence Database

Charalampos S. Kouzinopoulos, John-Alexander M. Assael, Themistoklis K. Pyrgiotis, Konstantinos G. Margaritis

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Tags: Algorithms, Computer science, CUDA, Databases, GPU cluster, MPI, nVidia, nVidia GeForce GT 240, Package, Tesla S1070

July 11, 2014 by hgpu

Massive Parallelism with GPUs for Centrality Ranking in Complex Networks

Frederico L. Cabral, Carla Osthoff, Rafael Nardes, Daniel Ramos

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Tags: Computer science, CUDA, GPU cluster, Graph theory, MPI, nVidia, Tesla K20

July 6, 2014 by hgpu

The Framework and Compilation Techniques for Directive-based GPU Cluster Programming

Pisit Makpaisit, Putchong Uthayopas

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Tags: Compilers, Computer science, CUDA, GPU cluster, nVidia, OpenACC, Tesla M2050

July 3, 2014 by hgpu

GPU accelerated Hybrid Tree Algorithm for Collision-less N-body Simulations

Tsuyoshi Watanabe, Naohito Nakasato

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Tags: Algorithms, Astrophysics, GPU cluster, Instrumentation and Methods for Astrophysics, N-body simulation, nVidia, OpenCL, Tesla M2090

June 25, 2014 by hgpu

Synergia CUDA: GPU-accelerated accelerator modeling package

Q. Lu, J. Amundson

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Tags: CUDA, FFT, GPU cluster, MPI, nVidia, Package, Particle-in-cell methods, Physics, Tesla C1070, Tesla K20

June 17, 2014 by hgpu

Scalable Lattice Boltzmann Solvers for CUDA GPU Clusters

Christian Obrecht, Frederic Kuznik, Bernard Tourancheau, Jean-Jacques Roux

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Tags: CUDA, Fluid dynamics, GPU cluster, Lattice Boltzmann model, MPI, nVidia, OpenMPI, Tesla M2070

June 15, 2014 by hgpu

GPPE: a GPU-based Parallel Processing Environment for Large Scale Concurrent Data Streams

Jianwei Cao, Qingkui Chen, Songlin Zhuang

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Tags: Cloud, Clustering, Computer science, CUDA, GPU cluster, H.264/AVC, MPI, nVidia, nVidia GeForce GTX 260, nVidia GeForce GTX 280, nVidia GeForce GTX 295, nVidia GeForce GTX 480

June 12, 2014 by hgpu

Accelerating the scoring module of mass spectrometry-based peptide identification using GPUs

You Li, Hao Chi, Leihao Xia, Xiaowen Chu

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Tags: Bioinformatics, Biology, CUDA, GPU cluster, nVidia, nVidia GeForce GTX 580, Spectrometry

May 12, 2014 by hgpu

Managing the Topology of Heterogeneous Cluster Nodes with Hardware Locality (hwloc)

Brice Goglin

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Tags: Computer science, CUDA, GPU cluster, Heterogeneous systems, nVidia, OpenMPI, Package, Xeon Phi

May 7, 2014 by hgpu

Multi-GPU Implementation of the Minimum Volume Simplex Analysis Algorithm for Hyperspectral Unmixing

Alexander Agathos, Jun Li, Dana Petcu, Antonio Plaza

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Tags: Algorithms, Computer science, CUDA, GPU cluster, nVidia, Sensing, Tesla M2070

April 29, 2014 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

Vivaldi: A Domain-Specific Language for Volume Processing and Visualization on Distributed Heterogeneous Systems

Infiniband-Verbs on GPU: A case study of controlling an Infiniband network device from the GPU

A Hybrid Parallel Implementation of the Aho-Corasick and Wu-Manber Algorithms Using NVIDIA CUDA and MPI Evaluated on a Biological Sequence Database

Massive Parallelism with GPUs for Centrality Ranking in Complex Networks

The Framework and Compilation Techniques for Directive-based GPU Cluster Programming

GPU accelerated Hybrid Tree Algorithm for Collision-less N-body Simulations

Synergia CUDA: GPU-accelerated accelerator modeling package

Scalable Lattice Boltzmann Solvers for CUDA GPU Clusters

Accelerating the scoring module of mass spectrometry-based peptide identification using GPUs

Managing the Topology of Heterogeneous Cluster Nodes with Hardware Locality (hwloc)

Multi-GPU Implementation of the Minimum Volume Simplex Analysis Algorithm for Hyperspectral Unmixing

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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