Search for dissertations about: "Automatic parallelization"
Showing result 1 - 5 of 13 swedish dissertations containing the words Automatic parallelization.
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1. Automatic Parallelization of Equation-Based Simulation Programs
Abstract : Modern equation-based object-oriented modeling languages which have emerged during the past decades make it easier to build models of large and complex systems. The increasing size and complexity of modeled systems requires high performance execution of the simulation code derived from such models. READ MORE
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2. Automatic and Explicit Parallelization Approaches for Equation Based Mathematical Modeling and Simulation
Abstract : The move from single-core processor systems to multi-core and manyprocessor systems comes with the requirement of implementing computations in a way that can utilize these multiple computational units efficiently. This task of writing efficient parallel algorithms will not be possible without improving programming languages and compilers to provide the supporting mechanisms. READ MORE
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3. Automatic Parallelization using Pipelining for Equation-Based Simulation Languages
Abstract : During the most recent decades modern equation-based object-oriented modeling and simulation languages, such as Modelica, have become available. This has made it easier to build complex and more detailed models for use in simulation. READ MORE
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4. Automatic Parallelization of Simulation Code from Equation Based Simulation Languages
Abstract : Modern state-of-the-art equation based object oriented modeling languages such as Modelica have enabled easy modeling of large and complex physical systems. When such complex models are to be simulated, simulation tools typically perform a number of optimizations on the underlying set of equations in the modeled system, with the goal of gaining better simulation performance by decreasing the equation system size and complexity. READ MORE
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5. Parallel Stochastic Estimation on Multicore Platforms
Abstract : The main part of this thesis concerns parallelization of recursive Bayesian estimation methods, both linear and nonlinear such. Recursive estimation deals with the problem of extracting information about parameters or states of a dynamical system, given noisy measurements of the system output and plays a central role in signal processing, system identification, and automatic control. READ MORE