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Performance Tuning for CUDA-Accelerated Neighborhood Denoising Filters

Ziyi Zheng, Wei Xu and Klaus Mueller

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Tags: Computed tomography, CT, CUDA, Filtering, Image processing, nVidia, nVidia GeForce GTX 480, Performance, Signal denoising

November 9, 2011 by hgpu

Effects of GPU and CPU Loads on Performance of CUDA Applications

Maksim Bobrov, Roy Melton, Stanislaw Radziszowski, Marcin Lukowiak

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Tags: AES, Algorithms, Computer science, CUDA, Hashing, nVidia, nVidia GeForce GTX 285, Performance, Security

November 9, 2011 by hgpu

Automatic transformation and optimization of applications on GPUs and GPU clusters

Wenjing Ma

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Tags: Algorithm optimization, Algorithms, Benchmarking, Code generation, Computer science, CUDA, Data mining, GPU cluster, Heterogeneous systems, nVidia, nVidia GeForce 8800 GTX, nVidia GeForce 9800 GX2, Optimization, Tesla T10, Thesis

November 9, 2011 by hgpu

Parallel Implementation of Niblack’s Binarization Approach on CUDA

Brij Mohan Singh, Rahul Sharma, Ankush Mittal, Debashish Ghosh

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Tags: Algorithms, Computer science, Computer vision, CUDA, Image processing, nVidia, nVidia GeForce 9500 GT, Pattern recognition

November 9, 2011 by hgpu

GPU-based Signal Processing Scheme for Bioinspired Optical Flow

Fermin Ayuso, Carlos Garcia, Guillermo Botella, Manuel Prieto, Francisco Tirado

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Tags: CUDA, Filtering, nVidia, Optical flow, Signal processing, Tesla C1060

November 8, 2011 by hgpu

PATUS: A Code Generation and Auto-Tuning Framework For Parallel Stencil Computations

Matthias Christen, Olaf Schenk, Helmar Burkhart

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Tags: Code generation, Computer science, CUDA, nVidia, Optimization, Package, Tesla C2050

November 8, 2011 by hgpu

GPU Cluster with MATLAB

A. Guillen, M. Garcia, L. J. Herrera, H. Pomares, I. Rojas

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Tags: Computer science, CUDA, GPU cluster, Heterogeneous systems, MPI, Nearest neighbour, nVidia, nVidia GeForce 8400 GS, nVidia GeForce 9800 GTX, nVidia GeForce GTS 450

November 8, 2011 by hgpu

Acceleration of Hessenberg Reduction for Nonsymmetric Eigenvalue Problems in a Hybrid CPU-GPU Computing Environment

Jun-ichi Muramatsu, Takeshi Fukaya, Shao-Liang Zhang, Kinji Kimura, Yusaku Yamamoto

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Tags: Algorithms, Computer science, CUBLAS, CUDA, Linear Algebra, nVidia, Tesla C1060

November 8, 2011 by hgpu

Graphics Processing Unit Utilization in Circuit Simulation

Mikko Hulkkonen

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Tags: Computer science, CUDA, Electronic design automation, nVidia, nVidia GeForce GTX 260, Thesis

November 8, 2011 by hgpu

Performance analysis of a hybrid MPI/CUDA implementation of the NASLU benchmark

S.J. Pennycook, S.D. Hammond, S.A. Jarvis, G.R. Mudalige

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Tags: Benchmarking, Computer science, CUDA, MPI, nVidia, nVidia GeForce 8400 GS, nVidia GeForce 9400 GT, Operating systems, Performance, Tesla C1060, Tesla C2050, Tesla T10

November 8, 2011 by hgpu

High performance massively parallel direct N-body simulations on large GPU clusters

Peter Berczik, Keigo Nitadori, Shiyan Zhong, Rainer Spurzem, Tsuyoshi Hamada, Xiaowei Wang, Ingo Berentzen, Alexander Veles, Wei Ge

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Tags: Astrophysics, CUDA, GPU cluster, MPI, N-body simulation, nVidia, Tesla C1060, Tesla C2050

November 8, 2011 by hgpu

The Infrared behavior of SU(3) Nf=12 gauge theory -about the existence of conformal fixed point-

Kenji Ogawa, Tatsumi Aoyama, Hiroaki Ikeda, Etsuko Itou, Masafumi Kurachi, C.-J. David Lin, Hideo Matsufuru, Hiroshi Ohki, Tetsuya Onogi, Eigo Shintani, Takeshi Yamazaki

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Tags: CUDA, GPU cluster, High Energy Physics - Lattice, nVidia, Physics, QCD, Tesla C1060

November 8, 2011 by hgpu

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

Kokkidio: Fast, expressive, portable code, based on Kokkos and Eigen

LLaMA-Inference-Bench

LLM-Inference-Bench: Inference Benchmarking of Large Language Models on AI Accelerators

MATAR

On a Simplified Approach to Achieve Parallel Performance and Portability Across CPU and GPU Architectures

Over-synchronization in GPU Programs

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

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