high performance computing on graphics processing units: hgpu.org

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NMF-mGPU: non-negative matrix factorization on multi-GPU systems

Edgardo Mejia-Roa, Daniel Tabas-Madrid, Javier Setoain, Carlos Garcia, Francisco Tirado, Alberto Pascual-Montano

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Tags: Algorithms, Bioinformatics, Biology, CUDA, Factorization, GPU cluster, MPI, Nonnegative matrix factorization, nVidia, Package, Tesla C1060

February 19, 2015 by hgpu

Locality-aware parallel block-sparse matrix-matrix multiplication using the Chunks and Tasks programming model

Emanuel H. Rubensson, Elias Rudberg

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Tags: Algorithms, Computer science, CUDA, Matrix multiplication, MPI, nVidia, Sparse matrix, Tesla K20

February 2, 2015 by hgpu

Simulating and Visualizing Real-Time Crowds on GPU Clusters

Benjamin Hernandez, Hugo Perez, Isaac Rudomin, Sergio Ruiz, Oriam DeGyves, Leonel Toledo

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Tags: Algorithms, Computer science, CUDA, GPU cluster, MPI, nVidia, nVidia GeForce GTX Titan, nVidia Jetson TK1, Rendering, Tesla M2090, Visualization

January 8, 2015 by hgpu

Optimising Hydrodynamics applications for the Cray XC30 with the application tool suite

W. P. Gaudin, A. C. Mallinson, O. Perks, J. A. Herdman, D. A. Beckingsale, J. M. Levesque, M. Boulton, S. McIntosh-Smith, S. A. Jarvis

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Tags: CUDA, Fluid dynamics, MPI, nVidia, OpenACC, OpenCL, Package, Tesla K20

December 18, 2014 by hgpu

Bamboo: Automatic Translation of MPI Source into a Latency-Tolerant Form

Nhat Tan Nguyen Thanh

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Tags: Computer science, CUDA, Linear Algebra, MPI, nVidia, Package, Tesla K20, Thesis

December 15, 2014 by hgpu

Strong scaling of general-purpose molecular dynamics simulations on GPUs

Jens Glaser, Trung Dac Nguyen, Joshua A. Anderson, Pak Lui, Filippo Spiga, Jaime A. Millan, David C. Morse, Sharon C. Glotzer

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Tags: Computational Physics, CUDA, Molecular dynamics, MPI, nVidia, Physics, Tesla K20

December 12, 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

Code Optimization on Kepler GPUs and Xeon Phi

Yong-Chull Jang, Hwancheol Jeong, Jangho Kim, Weonjong Lee, Jeonghwan Pak, Yuree Chung (SWME Collaboration)

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Tags: CUDA, High Energy Physics - Lattice, Intel Xeon Phi, Maxwell's equations, MPI, nVidia, nVidia GeForce GTX 980, nVidia GeForce GTX Titan, OpenMP, Performance, Physics, QCD, Tesla K40

November 12, 2014 by hgpu

Highly optimized simulations on single- and multi-GPU systems of 3D Ising spin glass

Matteo Lulli, Massimo Bernaschi, Giorgio Parisi

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Tags: Condensed matter, CUDA, Disordered Systems and Neural Networks, Ising model, MPI, nVidia, nVidia GeForce GTX Titan, Pseudo-random number generators

November 5, 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

Multi-GPU Based Lattice Boltzmann Method for Hemodynamic Simulation in Patient-Specific Cerebral Aneurysm

Changsheng Huang, Baochang Shi, Zhaoli Guo, Zhenhua Chai

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Tags: Algorithms, CUDA, Fluid dynamics, Lattice Boltzmann model, MPI, nVidia, Package, Tesla C1060, Tesla K20

October 16, 2014 by hgpu

Scalable approximate k-NN in multidimensional big data

Hisham Mohamed

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Tags: Algorithms, Computer science, CUDA, Data mining, Data Structures and Algorithms, Information Retrieval, Machine learning, MapReduce, MPI, Nearest neighbour, nVidia, nVidia Quadro NVS 5200 M, Thesis, Visualization

October 13, 2014 by hgpu

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Accelerating a Linear Programming Algorithm on AMD GPUs

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Towards Efficient and Practical GPU Multitasking in the Era of LLM

Bandicoot: C++ library for GPU accelerated linear algebra

Bandicoot: A Templated C++ Library for GPU Linear Algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

The Fused Kernel Library: A C++ API to Develop Highly-Efficient GPU Libraries

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

Block: Balance Loader of LLM Serving with Context, Knowledge and Predictive Scheduling

Block: Balancing Load in LLM Serving with Context, Knowledge and Predictive Scheduling

SIGMo: Scalable Isomorphism Graph Matching on GPUs

SIGMo: High-Throughput Batched Subgraph Isomorphism on GPUs for Molecular Matching

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

DGEMM without FP64 Arithmetic – using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

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high performance computing on graphics processing units: hgpu.org

NMF-mGPU: non-negative matrix factorization on multi-GPU systems

Locality-aware parallel block-sparse matrix-matrix multiplication using the Chunks and Tasks programming model

Simulating and Visualizing Real-Time Crowds on GPU Clusters

Optimising Hydrodynamics applications for the Cray XC30 with the application tool suite

Bamboo: Automatic Translation of MPI Source into a Latency-Tolerant Form

Strong scaling of general-purpose molecular dynamics simulations on GPUs

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

Code Optimization on Kepler GPUs and Xeon Phi

Highly optimized simulations on single- and multi-GPU systems of 3D Ising spin glass

Performance Modeling, Optimization, and Characterization on Heterogeneous Architectures

Multi-GPU Based Lattice Boltzmann Method for Hemodynamic Simulation in Patient-Specific Cerebral Aneurysm

Scalable approximate k-NN in multidimensional big data

Recent source codes

torchPDLP: Primal-Dual Linear Programming in PyTorch. In collaboration with AMD and IPAM

Benchmarks for Dissecting CPU-GPU Unified Physical Memory on AMD MI300A APUs

kvcached: Elastic KV cache for dynamic GPU sharing and efficient multi-LLM inference

Bandicoot: C++ library for GPU accelerated linear algebra

Luthier: Bridging Auto-Tuning and Vendor Libraries for Efficient Deep Learning Inference

Fused Kernel Library (FKL)

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

Block: Balance Loader of LLM Serving with Context, Knowledge and Predictive Scheduling

SIGMo: Scalable Isomorphism Graph Matching on GPUs

DGEMM without FP64 Arithmetic - using FP64 Emulation and FP8 Tensor Cores with Ozaki Scheme

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