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Simulations of Large Membrane Regions using GPU-enabled Computations – Preliminary Results

Narayan Ganesan, Michela Taufer, Sandeep Patel

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Tags: Chemistry, CUDA, Membrane computing, Molecular dynamics, nVidia, Performance

February 17, 2011 by hgpu

Dynamically scheduled Cholesky factorization on multicore architectures with GPU accelerators

Emmanuel Agullo, Cedric Augonnet, Jack Dongarra, Hatem Ltaief, Raymond Namyst, Jean Roman, Samuel Thibault, Stanimire Tomov

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Tags: Computer science, CUDA, Linear Algebra, nVidia, nVidia Quadro FX 5800, Task scheduling

February 17, 2011 by hgpu

A Strategy for Automatically Generating High Performance CUDA Code for a GPU Accelerator from a Specialized Fortran Code Expression

Pei-Hung Lin, Jagan Jayaraj, and Paul R. Woodward

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Tags: Cell processor, Code generation, Compilers, Computer science, CUDA, Fortran, High-level Languages, Memory model, nVidia, Tesla C1060

February 17, 2011 by hgpu

Accelerating Algorithms on GPUs in SCIRun: the Conjugate Gradient Case Study

Devon Yablonski, Miriam Leeser, Dana Brooks

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Tags: Computer science, Conjugate gradient solver, CUDA, nVidia, nVidia GeForce GTX 280, Package, Sparse matrix

February 17, 2011 by hgpu

Takagi Factorization on GPU using CUDA

Gagandeep S. Sachdev, Vishay Vanjani and Mary W. Hall

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Tags: Computer science, CUDA, Factorization, Matrix decomposition, nVidia, nVidia GeForce GTX 260

February 17, 2011 by hgpu

Automatically Tuned Dense Linear Algebra for Multicore+GPU

Xing Fu, Xue Li, Gregory D. Peterson

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Tags: Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 280, Package

February 17, 2011 by hgpu

GpuC: Data parallel language extension to CUDA

Zeki Bozkus

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Tags: Compilers, Computer science, CUDA, High-level Languages, nVidia, OpenMP, Optimization

February 16, 2011 by hgpu

Enhancing the simulation of P systems for the SAT problem on GPUs

J.M. Cecilia, J.M. Garcia, G.D. Guerrero, M.A. Martinez-Amor, M.J. Perez-Jimenez, M. Ujaldon

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Tags: Biology, CUDA, nVidia, P systems, SAT, Tesla C1060

February 16, 2011 by hgpu

Accelerating the Stochastic Simulation Algorithm using Emerging Architectures

David Dewayne Jenkins

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Tags: Biology, CUDA, Monte Carlo simulation, nVidia, nVidia GeForce 8600 M, Stochastic simulation, Tesla C1060, Tesla C870, Thesis

February 16, 2011 by hgpu

GPU Accelerated Stochastic Simulation

David D. Jenkins, Gregory D. Peterson

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Tags: Biology, CUDA, Monte Carlo simulation, nVidia, nVidia GeForce GTX 480, Stochastic simulation, Tesla C1060

February 16, 2011 by hgpu

A GPU-based Flood Simulation Framework

Siddharth Shankar, Alfred J. Kalyanapu, Charles D. Hansen, Steven J. Burian

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Tags: CUDA, Fluid dynamics, nVidia, nVidia GeForce 8400 GS, Tesla T10

February 16, 2011 by hgpu

Static Memory Access Pattern Analysis on a Massively Parallel GPU

Byunghyun Jang, Dana Schaa, Perhaad Mistry, and David Kaeli

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Tags: Computer science, Matrix multiplication, Memory model, nVidia, nVidia GeForce 8800 Ultra, nVidia GeForce GTX 285, OpenCL, Optimization

February 16, 2011 by hgpu

PROM: an open-source software framework to enhance the robustness and performance of predictive models against such changes during deployment

Enhancing Deployment-Time Predictive Model Robustness for Code Analysis and Optimization

DeepSpeed: a deep learning optimization library that makes distributed training and inference easy, efficient, and effective

Scalable Access-Pattern Aware I/O Acceleration and Multi-Tiered Data Management for HPC and AI Workloads

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

SW#SYCL

Analyzing the Performance Portability of SYCL across CPUs, GPUs, and Hybrid Systems with Protein Database Search

tdg-benchs: benchmarks used to test the performance of taskgraph

Leveraging the potential of task-based programming with OpenMP task graphs

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

Simulations of Large Membrane Regions using GPU-enabled Computations – Preliminary Results

Dynamically scheduled Cholesky factorization on multicore architectures with GPU accelerators

A Strategy for Automatically Generating High Performance CUDA Code for a GPU Accelerator from a Specialized Fortran Code Expression

Accelerating Algorithms on GPUs in SCIRun: the Conjugate Gradient Case Study

Takagi Factorization on GPU using CUDA

Automatically Tuned Dense Linear Algebra for Multicore+GPU

GpuC: Data parallel language extension to CUDA

Enhancing the simulation of P systems for the SAT problem on GPUs

Accelerating the Stochastic Simulation Algorithm using Emerging Architectures

GPU Accelerated Stochastic Simulation

A GPU-based Flood Simulation Framework

Static Memory Access Pattern Analysis on a Massively Parallel GPU

Recent source codes

PROM: an open-source software framework to enhance the robustness and performance of predictive models against such changes during deployment

DeepSpeed: a deep learning optimization library that makes distributed training and inference easy, efficient, and effective

HPX: a C++ Standard Library for Concurrency and Parallelism

TorchQC: Quantum Dynamics and Machine Learning

Matrix multiplication using Tensor Cores in CUDA

CPP Joules: Energy Measurement tool for CPP/CUDA programs

HPC-Coder-v2

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

SW#SYCL

tdg-benchs: benchmarks used to test the performance of taskgraph

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