high performance computing on graphics processing units: hgpu.org

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Architectural Comparisons for a Quantum Monte Carlo Application

Akila Gothandaraman, Rick Weber, Gregory D. Peterson, Robert J. Hinde, Robert J. Harrison

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Tags: AMD FireStream 9170, ATI, Brook, Computer science, CUDA, FPGA, Monte Carlo simulation, nVidia, QMC, Tesla C1060

February 23, 2011 by hgpu

Flexible Hardware Mapping for Finite Element Simulations on Hybrid CPU / GPU Clusters

Aaron Becker, Isaac Dooley, Laxmikant V. Kale

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Tags: Computer science, CUDA, Finite element method, GPU cluster, nVidia, Tesla S1070

February 23, 2011 by hgpu

Probing biomolecular machines with graphics processors

James C. Phillips, John E. Stone

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Tags: Biology, Biomolecules, CUDA, GPU cluster, Molecular simulation, nVidia, OpenCL, Review, Tesla S1070

February 23, 2011 by hgpu

GPU Acceleration of the Generalized Interpolation Material Point Method

Wei-Fan Chiang, Michael DeLisi, Todd Hummel, Tyler Prete, Kevin Tew, Mary Hall, Phil Wallstedt, James Guilkey

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Tags: CUDA, nVidia, nVidia GeForce 9600 GT, Particle-in-cell methods, Physics

February 22, 2011 by hgpu

Accelerating Energy Minimization using Graphics Processors

Bharat Sukhwani, Martin C. Herbordt

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Tags: Chemistry, CUDA, Molecular modeling, nVidia, Tesla C1060

February 22, 2011 by hgpu

Accelerating the ANSYS Direct Sparse Solver with GPUs

Geraud P. Krawezik, Gene Poole

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Tags: Computer science, CUDA, Linear Algebra, Mixed precision, nVidia, Sparse direct solvers, Tesla C1060

February 22, 2011 by hgpu

Production Floating Point Applications on FPGAs

Martin C. Herbordt, Bharat Sukhwani, Matt Chiu, Md. Ashfaq Khan

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Tags: Chemistry, Computer science, CUDA, FPGA, Molecular dynamics, Molecular modeling, nVidia, Tesla C1060

February 22, 2011 by hgpu

Performance analysis and optimization of three-dimensional FDTD on GPU using roofline model

Ki-Hwan Kim, KyoungHo Kim, Q-Han Park

Tags: Computer science, CUDA, FDTD, Finite-difference time-domain, nVidia, nVidia GeForce GTX 480

February 22, 2011 by hgpu

Data Structures and Transformations for Physically Based Simulation on a GPU

Perhaad Mistry, Dana Schaa, Byunghyun Jang, David Kaeli, Albert Dvornik, Dwight Meglan

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Tags: Computer science, CUDA, Data Structures and Algorithms, nVidia, nVidia GeForce GTX 285, Physics-based simulation

February 22, 2011 by hgpu

GPU Acceleration of Runge-Kutta Integrators

Lawrence Murray

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Tags: Algorithms, CUDA, Mathematics, nVidia, ODEs, Ordinary differential equations

February 22, 2011 by hgpu

Software-Based ECC for GPUs

Naoya Maruyama, Akira Nukada, Satoshi Matsuoka

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Tags: Computer science, CUDA, Error recovery, FFT, N-body simulation, nVidia, nVidia GeForce 8800 GTS, nVidia GeForce GTX 285, Tesla S1070

February 21, 2011 by hgpu

An Automated Approach for SIMD Kernel Generation for GPU based Software Acceleration

Kanupriya Gulati and Sunil P Khatri

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Tags: Code generation, Compilers, Computer science, CUDA, nVidia, nVidia GeForce GTX 280

February 21, 2011 by hgpu

Tutoring LLM into a Better CUDA Optimizer

Adaptivity in AdaptiveCpp: Optimizing Performance by Leveraging Runtime Information During JIT-Compilation

Kernel Library for LLM Serving

Compiler and Runtime Systems for Generative AI Models

Neptune: Advanced ML Operator Fusion for Locality and Parallelism on GPUs

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high performance computing on graphics processing units: hgpu.org

Architectural Comparisons for a Quantum Monte Carlo Application

Flexible Hardware Mapping for Finite Element Simulations on Hybrid CPU / GPU Clusters

Probing biomolecular machines with graphics processors

GPU Acceleration of the Generalized Interpolation Material Point Method

Accelerating Energy Minimization using Graphics Processors

Accelerating the ANSYS Direct Sparse Solver with GPUs

Production Floating Point Applications on FPGAs

Performance analysis and optimization of three-dimensional FDTD on GPU using roofline model

Data Structures and Transformations for Physically Based Simulation on a GPU

GPU Acceleration of Runge-Kutta Integrators

Software-Based ECC for GPUs

An Automated Approach for SIMD Kernel Generation for GPU based Software Acceleration

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