high performance computing on graphics processing units: hgpu.org

hgpu.org » Probabilistic model checking

PRISM-PSY: Precise GPU-Accelerated Parameter Synthesis for Stochastic Systems

Milan Ceska, Petr Pilar, Nicola Paoletti, Lubos Brim, Marta Kwiatkowska

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Tags: Algorithms, Computer science, nVidia, nVidia GeForce GTX 480, OpenCL, Probabilistic model checking

February 6, 2016 by hgpu

A Comparison of Sequential and GPU Implementations of Iterative Methods to Compute Reachability Probabilities

Elise Cormie-Bowins

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Tags: Computer science, CUDA, Logic in Computer Science, nVidia, nVidia GeForce GTX 260, Probabilistic model checking

October 25, 2012 by hgpu

Improving GPU Sparse Matrix-Vector Multiplication for Probabilistic Model Checking

Anton J. Wijs, Dragan Bosnacki

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 480, Package, Probabilistic model checking, Sparse matrix

August 6, 2012 by hgpu

Large scale parallel state space search utilizing graphics processing units and solid state disks

Damian Sulewski

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Tags: Algorithms, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 285, Probabilistic model checking, Search strategies, Thesis

May 11, 2012 by hgpu

Designing Fast LTL Model Checking Algorithms for Many-Core GPUs

Jiri Barnat, Petr Bauch, Lubos Brim, and Milan Ceska

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Tags: Algorithms, Computer science, CUDA, Memory model, nVidia, nVidia GeForce GTX 480, Probabilistic model checking

January 24, 2012 by hgpu

Parallel probabilistic model checking on general purpose graphics processors

Dragan Bosnacki, Stefan Edelkamp, Damian Sulewski, Anton Wijs

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Tags: Algorithms, Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 285, Probabilistic model checking

October 2, 2011 by hgpu

GPU-PRISM: An Extension of PRISM for General Purpose Graphics Processing Units

Dragan Bosnacki, Stefan Edelkamp, Damian Sulewski, Anton Wijs

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Tags: Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 285, Probabilistic model checking

May 19, 2011 by hgpu

Efficient Probabilistic Model Checking on General Purpose Graphics Processors

Dragan Bosnacki, Stefan Edelkamp, Damian Sulewski

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 280, Probabilistic model checking

November 23, 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

PRISM-PSY: Precise GPU-Accelerated Parameter Synthesis for Stochastic Systems

A Comparison of Sequential and GPU Implementations of Iterative Methods to Compute Reachability Probabilities

Improving GPU Sparse Matrix-Vector Multiplication for Probabilistic Model Checking

Large scale parallel state space search utilizing graphics processing units and solid state disks

Designing Fast LTL Model Checking Algorithms for Many-Core GPUs

Parallel probabilistic model checking on general purpose graphics processors

GPU-PRISM: An Extension of PRISM for General Purpose Graphics Processing Units

Efficient Probabilistic Model Checking on General Purpose Graphics Processors

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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