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Exploiting Heterogeneous Computing Platforms By Cataloging Best Solutions For Resource Intensive Seismic Applications

Thomas Grosser, Alexandros Gremm, Sebastian Veith, Gerald Heim, Wolfgang Rosenstiel, Victor Medeiros, Manoel Eusebio de Lima

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Tags: Earth and Space Sciences, FPGA, Geoscience, Heterogeneous systems, nVidia, OpenCL, Optimization, Seismic modeling, Seismology, Tesla T10P

September 25, 2011 by hgpu

A CUDA SIMT Interpreter for Genetic Programming

W. B. Langdon

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Tags: Computer science, CUDA, Genetic programming, nVidia, Package, Tesla T10P

February 15, 2011 by hgpu

Model-driven autotuning of sparse matrix-vector multiply on GPUs

Jee W. Choi, Amik Singh, Richard W. Vuduc

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, nVidia, Performance, Sparse matrix, Tesla C1060, Tesla C870, Tesla T10P

February 5, 2011 by hgpu

A CUDA SIMT interpreter for genetic programming. Revised

William B. Langdon

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Tags: Computer science, CUDA, Genetic programming, nVidia, Package, Tesla T10P

January 21, 2011 by hgpu

Exploring new architectures in accelerating CFD for Air Force applications

Jack Dongarra, Shirley Moore, Gregory Peterson, Stanimire Tomov

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Tags: Algorithms, Fluid dynamics, FPGA, nVidia, nVidia Quadro FX 5600, Tesla T10P

January 11, 2011 by hgpu

Power Consumption of GPUs from a Software Perspective

Sylvain Collange, David Defour, Arnaud Tisserand

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Tags: Computer science, CUDA, Energy-efficient computing, nVidia, nVidia GeForce 9800 GX2, Tesla C870, Tesla D870, Tesla T10P

January 7, 2011 by hgpu

Solving Sparse Linear Systems on NVIDIA Tesla GPUs

Mingliang Wang, Hector Klie, Manish Parashar, Hari Sudan

Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Sparse matrix, Tesla T10P

November 27, 2010 by hgpu

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

EnergyUCB-Bandit

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

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high performance computing on graphics processing units: hgpu.org

Exploiting Heterogeneous Computing Platforms By Cataloging Best Solutions For Resource Intensive Seismic Applications

A CUDA SIMT Interpreter for Genetic Programming

Model-driven autotuning of sparse matrix-vector multiply on GPUs

A CUDA SIMT interpreter for genetic programming. Revised

Exploring new architectures in accelerating CFD for Air Force applications

Power Consumption of GPUs from a Software Perspective

Solving Sparse Linear Systems on NVIDIA Tesla GPUs

Recent source codes

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

LLaMA-Inference-Bench

MATAR

Over-synchronization in GPU Programs

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

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

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

EnergyUCB-Bandit

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