high performance computing on graphics processing units: hgpu.org

hgpu.org » GPU cluster

24.77 Pflops on a Gravitational Tree-Code to Simulate the Milky Way Galaxy with 18600 GPUs

Jeroen Bedorf, Evghenii Gaburov, Michiko S. Fujii, Keigo Nitadori, Tomoaki Ishiyama, Simon Portegies Zwart

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Tags: Algorithms, Astrophysics, CUDA, GPU cluster, Gravitation, Instrumentation and Methods for Astrophysics, nVidia, Tesla K20

December 3, 2014 by hgpu

Performance Analysis of a High-level Abstractions-based Hydrocode on Future Computing Systems

G.R. Mudalige, I.Z. Reguly, M.B. Giles, A.C. Mallinson, W.P. Gaudin, J.A. Herdman

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Tags: Code generation, Computer science, CUDA, GPU cluster, MPI, nVidia, OpenACC, OpenCL, Tesla K20

December 1, 2014 by hgpu

A Fast Poisson Solver with Periodic Boundary Conditions for GPU Clusters in Various Configurations

Dale Nicholas Rattermann

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Tags: CUDA, FFT, Fluid dynamics, GPU cluster, Laplace and Poisson equation, nVidia, Poisson equation, Tesla M2050, Tesla M2070, Thesis

November 3, 2014 by hgpu

Performance Modeling, Optimization, and Characterization on Heterogeneous Architectures

Lokendra Singh Panwar

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Tags: ATI, ATI Radeon HD 5870, ATI Radeon HD 7970, Computational Complexity, Computer science, CUDA, Finite difference, GPU cluster, Heterogeneous systems, MPI, nVidia, OpenCL, Seismology, Tesla C1060, Tesla C2050, Thesis

October 29, 2014 by hgpu

A Complete and Efficient CUDA-Sharing Solution for HPC Clusters

Antonio J. Pena, Carlos Reano, Federico Silla, Rafael Mayo, Enrique S. Quintana-Orti, Jose Duato

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Tags: Computer science, CUDA, GPU cluster, nVidia, Tesla K20, Virtualization

October 14, 2014 by hgpu

Scalability Analysis of Parallel Algorithms on GPU Clusters

Fengshun Lu, Yufei Pang, Fukang Yin

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Tags: Algorithms, Benchmarking, Computer science, CUDA, GPU cluster, nVidia, Tesla M2050

September 25, 2014 by hgpu

High-accuracy Optimization by Parallel Iterative Discrete Approximation and GPU Cluster Computing

Di Zhao

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Tags: Cluster computing, Computer science, CUDA, GPU cluster, Machine learning, MPI, nVidia, nVidia GeForce GTX 660

September 16, 2014 by hgpu

Machine learning for ultrafast X-ray diffraction patterns on large-scale GPU clusters

Tomas Ekeberg, Stefan Engblom, Jing Liu

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Tags: Algorithms, Biological Physics, Biology, Biomolecules, Cluster computing, Computational Complexity, CUDA, GPU cluster, Machine learning, nVidia, nVidia GeForce GTX 680, OpenMPI

September 16, 2014 by hgpu

Parallel Breadth First Search on GPU Clusters

Zhisong Fu, Harish Kumar Dasari, Martin Berzins, Bryan Thompson

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Tags: Algorithms, Computer science, CUDA, GPU cluster, Graph theory, Network communications, nVidia, Package, Tesla K20

August 11, 2014 by hgpu

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

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

BoltzGen:Toward Universal Binder Design

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

tritonBLAS: Triton-based Analytical Approach for GEMM Kernel Parameter Selection

See all packages

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high performance computing on graphics processing units: hgpu.org

24.77 Pflops on a Gravitational Tree-Code to Simulate the Milky Way Galaxy with 18600 GPUs

Performance Analysis of a High-level Abstractions-based Hydrocode on Future Computing Systems

A Fast Poisson Solver with Periodic Boundary Conditions for GPU Clusters in Various Configurations

Performance Modeling, Optimization, and Characterization on Heterogeneous Architectures

A Complete and Efficient CUDA-Sharing Solution for HPC Clusters

Scalability Analysis of Parallel Algorithms on GPU Clusters

High-accuracy Optimization by Parallel Iterative Discrete Approximation and GPU Cluster Computing

Machine learning for ultrafast X-ray diffraction patterns on large-scale GPU clusters

Parallel Breadth First Search on GPU Clusters

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

Recent source codes

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

BoltzGen:Toward Universal Binder Design

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

tritonBLAS: A Lightweight Triton-based General Matrix Multiplication (GEMM) Library

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