high performance computing on graphics processing units: hgpu.org

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Nonlinear Dynamic Analysis Efficiency by Using a GPU Parallelization

Hong-yu Li, Jun Teng, Zuo-hua Li, Lu Zhang

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Tags: Computer science, CUDA, FEM, Finite element method, nVidia, nVidia GeForce GT 430, nVidia GeForce GT 720 M, nVidia GeForce GTX 460

December 8, 2015 by hgpu

Using Data Compression for Increasing Efficiency of Data Transfer Between Main Memory and Intel Xeon Phi Coprocessor or NVidia GPU in Parallel DBMS

Konstantin Y. Besedin, Pavel S. Kostenetskiy, Stepan O. Prikazchikov

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Tags: Algorithms, Compression, Computer science, CUDA, Databases, Intel Xeon Phi, nVidia, OpenMP, Tesla K40

December 6, 2015 by hgpu

A Study of Parallel Sorting Algorithms Using CUDA and OpenMP

Hakan Gokahmetoglu

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Tags: Algorithms, Computational Complexity, Computer science, CUDA, nVidia, nVidia GeForce GTX 850 M, OpenMP, Sorting, Thesis

December 6, 2015 by hgpu

Parallel Implementation of Vortex Element Method on CPUs and GPUs

Kseniia Kuzmina, Ilia Marchevsky, Victoriya Moreva

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Tags: CUDA, Fast multipole method, Fluid dynamics, MPI, nVidia, nVidia GeForce GTX 970, Tesla C2070

December 6, 2015 by hgpu

CuMF: scale matrix factorization using just ONE machine with GPUs

Wei Tan, Liangliang Cao

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Tags: Computer science, CUDA, Data parallelism, Factorization, Linear Algebra, nVidia, nVidia GeForce GTX Titan X

December 6, 2015 by hgpu

Parallelization Methods of the Template Matching Method on Graphics Accelerators

Gabor Kertesz, Sandor Szenasi, Zoltan Vamossy

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Tags: Algorithms, Computer science, CUDA, Image processing, nVidia, Tesla K40

December 6, 2015 by hgpu

The Genetic Convolutional Neural Network Model Based on Random Sample

You Zhining, Pu Yunming

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Tags: Algorithms, CNN, Computer science, CUDA, Deep learning, Genetic algorithm, Neural networks, nVidia, nVidia GeForce GTX 770

December 4, 2015 by hgpu

Optimizing CUDA Shared Memory Usage

Shuang Gao, Gregory D. Peterson

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Tags: Computer science, CUDA, nVidia, Optimization, Poster

December 4, 2015 by hgpu

An Efficient Parallel Algorithm for Graph Isomorphism on GPU using CUDA

Min-Young Son, Young-Hak Kim, Byoung-Woo Oh

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Tags: Computer science, CUDA, Graph theory, nVidia, nVidia GeForce GTX 670

December 4, 2015 by hgpu

Programming in CUDA for Kepler and Maxwell Architecture

Esteban G. W. Clua, Marcelo Zamith

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Tags: Computer science, CUDA, nVidia, Performance

December 1, 2015 by hgpu

Auxiliary Image Regularization for Deep CNNs with Noisy Labels

Samaneh Azadi, Jiashi Feng, Stefanie Jegelka, Trevor Darrell

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Tags: CNN, Computer science, Computer vision, CUDA, Deep learning, Neural networks, nVidia

December 1, 2015 by hgpu

A General Framework for Constrained Bayesian Optimization using Information-based Search

Jose Miguel Hernandez-Lobato, Michael A. Gelbart, Ryan P. Adams, Matthew W. Hoffman, Zoubin Ghahramani

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Tags: Bayesian, Computer science, CUDA, Machine learning, nVidia, nVidia GeForce GTX 580, Package, Python

December 1, 2015 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

Nonlinear Dynamic Analysis Efficiency by Using a GPU Parallelization

Using Data Compression for Increasing Efficiency of Data Transfer Between Main Memory and Intel Xeon Phi Coprocessor or NVidia GPU in Parallel DBMS

A Study of Parallel Sorting Algorithms Using CUDA and OpenMP

Parallel Implementation of Vortex Element Method on CPUs and GPUs

CuMF: scale matrix factorization using just ONE machine with GPUs

Parallelization Methods of the Template Matching Method on Graphics Accelerators

The Genetic Convolutional Neural Network Model Based on Random Sample

Optimizing CUDA Shared Memory Usage

An Efficient Parallel Algorithm for Graph Isomorphism on GPU using CUDA

Programming in CUDA for Kepler and Maxwell Architecture

Auxiliary Image Regularization for Deep CNNs with Noisy Labels

A General Framework for Constrained Bayesian Optimization using Information-based Search

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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