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custom source code transformation tool  (OpenSim Ltd)

 
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    OpenSim Ltd custom source code transformation tool
    We developed two approaches (AD-ADOLC and AD-Recorder) to make an OpenSim function F and its forward ( F fwd ) and reverse ( F rev ) directional derivatives available within the CasADi environment for use by the NLP solver during the optimization. In the AD-ADOLC approach (top), ADOL-C’s algorithms are used in a C++ <t>code</t> to provide F fwd and F rev . In the AD-Recorder approach (bottom), Recorder provides the expression graph of F as MATLAB <t>source</t> code from which CasADi’s C-code generator generates C-code containing F , F fwd , and F rev . The AD-Recorder approach combines operator overloading, when generating the expression graph, and source code <t>transformation,</t> when processing the expression graph to generate C-code for F , F fwd , and F rev . In both approaches, the code comprising F , F fwd , and F rev is compiled as a Dynamic-link Library (DLL), which is imported as an external function within the CasADi environment. In our application, F represents the multi-body dynamics and is called when formulating the optimal control problem. The latter is then composed into a differentiable optimal control transcription using CasADi. During the optimization, CasADi provides the NLP solver with evaluations of the NLP objective function ( nlp f ), constraints ( nlp g ), objective function gradient ( nlp grad f ), constraint Jacobian ( nlp jac g ), and Hessian of the Lagrangian ( nlp hess l ). CasADi efficiently queries F fwd and F rev to construct the full derivative matrices.
    Custom Source Code Transformation Tool, supplied by OpenSim Ltd, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/custom source code transformation tool/product/OpenSim Ltd
    Average 90 stars, based on 1 article reviews
    custom source code transformation tool - by Bioz Stars, 2026-04
    90/100 stars

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    1) Product Images from "Algorithmic differentiation improves the computational efficiency of OpenSim-based trajectory optimization of human movement"

    Article Title: Algorithmic differentiation improves the computational efficiency of OpenSim-based trajectory optimization of human movement

    Journal: PLoS ONE

    doi: 10.1371/journal.pone.0217730

    We developed two approaches (AD-ADOLC and AD-Recorder) to make an OpenSim function F and its forward ( F fwd ) and reverse ( F rev ) directional derivatives available within the CasADi environment for use by the NLP solver during the optimization. In the AD-ADOLC approach (top), ADOL-C’s algorithms are used in a C++ code to provide F fwd and F rev . In the AD-Recorder approach (bottom), Recorder provides the expression graph of F as MATLAB source code from which CasADi’s C-code generator generates C-code containing F , F fwd , and F rev . The AD-Recorder approach combines operator overloading, when generating the expression graph, and source code transformation, when processing the expression graph to generate C-code for F , F fwd , and F rev . In both approaches, the code comprising F , F fwd , and F rev is compiled as a Dynamic-link Library (DLL), which is imported as an external function within the CasADi environment. In our application, F represents the multi-body dynamics and is called when formulating the optimal control problem. The latter is then composed into a differentiable optimal control transcription using CasADi. During the optimization, CasADi provides the NLP solver with evaluations of the NLP objective function ( nlp f ), constraints ( nlp g ), objective function gradient ( nlp grad f ), constraint Jacobian ( nlp jac g ), and Hessian of the Lagrangian ( nlp hess l ). CasADi efficiently queries F fwd and F rev to construct the full derivative matrices.
    Figure Legend Snippet: We developed two approaches (AD-ADOLC and AD-Recorder) to make an OpenSim function F and its forward ( F fwd ) and reverse ( F rev ) directional derivatives available within the CasADi environment for use by the NLP solver during the optimization. In the AD-ADOLC approach (top), ADOL-C’s algorithms are used in a C++ code to provide F fwd and F rev . In the AD-Recorder approach (bottom), Recorder provides the expression graph of F as MATLAB source code from which CasADi’s C-code generator generates C-code containing F , F fwd , and F rev . The AD-Recorder approach combines operator overloading, when generating the expression graph, and source code transformation, when processing the expression graph to generate C-code for F , F fwd , and F rev . In both approaches, the code comprising F , F fwd , and F rev is compiled as a Dynamic-link Library (DLL), which is imported as an external function within the CasADi environment. In our application, F represents the multi-body dynamics and is called when formulating the optimal control problem. The latter is then composed into a differentiable optimal control transcription using CasADi. During the optimization, CasADi provides the NLP solver with evaluations of the NLP objective function ( nlp f ), constraints ( nlp g ), objective function gradient ( nlp grad f ), constraint Jacobian ( nlp jac g ), and Hessian of the Lagrangian ( nlp hess l ). CasADi efficiently queries F fwd and F rev to construct the full derivative matrices.

    Techniques Used: Expressing, Transformation Assay, Control, Construct



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    custom source code transformation tool  (OpenSim Ltd)
    90
    OpenSim Ltd custom source code transformation tool
    We developed two approaches (AD-ADOLC and AD-Recorder) to make an OpenSim function F and its forward ( F fwd ) and reverse ( F rev ) directional derivatives available within the CasADi environment for use by the NLP solver during the optimization. In the AD-ADOLC approach (top), ADOL-C’s algorithms are used in a C++ <t>code</t> to provide F fwd and F rev . In the AD-Recorder approach (bottom), Recorder provides the expression graph of F as MATLAB <t>source</t> code from which CasADi’s C-code generator generates C-code containing F , F fwd , and F rev . The AD-Recorder approach combines operator overloading, when generating the expression graph, and source code <t>transformation,</t> when processing the expression graph to generate C-code for F , F fwd , and F rev . In both approaches, the code comprising F , F fwd , and F rev is compiled as a Dynamic-link Library (DLL), which is imported as an external function within the CasADi environment. In our application, F represents the multi-body dynamics and is called when formulating the optimal control problem. The latter is then composed into a differentiable optimal control transcription using CasADi. During the optimization, CasADi provides the NLP solver with evaluations of the NLP objective function ( nlp f ), constraints ( nlp g ), objective function gradient ( nlp grad f ), constraint Jacobian ( nlp jac g ), and Hessian of the Lagrangian ( nlp hess l ). CasADi efficiently queries F fwd and F rev to construct the full derivative matrices.
    Custom Source Code Transformation Tool, supplied by OpenSim Ltd, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/custom source code transformation tool/product/OpenSim Ltd
    Average 90 stars, based on 1 article reviews
    custom source code transformation tool - by Bioz Stars, 2026-04
    90/100 stars
    		  Buy from Supplier

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    We developed two approaches (AD-ADOLC and AD-Recorder) to make an OpenSim function F and its forward ( F fwd ) and reverse ( F rev ) directional derivatives available within the CasADi environment for use by the NLP solver during the optimization. In the AD-ADOLC approach (top), ADOL-C’s algorithms are used in a C++ code to provide F fwd and F rev . In the AD-Recorder approach (bottom), Recorder provides the expression graph of F as MATLAB source code from which CasADi’s C-code generator generates C-code containing F , F fwd , and F rev . The AD-Recorder approach combines operator overloading, when generating the expression graph, and source code transformation, when processing the expression graph to generate C-code for F , F fwd , and F rev . In both approaches, the code comprising F , F fwd , and F rev is compiled as a Dynamic-link Library (DLL), which is imported as an external function within the CasADi environment. In our application, F represents the multi-body dynamics and is called when formulating the optimal control problem. The latter is then composed into a differentiable optimal control transcription using CasADi. During the optimization, CasADi provides the NLP solver with evaluations of the NLP objective function ( nlp f ), constraints ( nlp g ), objective function gradient ( nlp grad f ), constraint Jacobian ( nlp jac g ), and Hessian of the Lagrangian ( nlp hess l ). CasADi efficiently queries F fwd and F rev to construct the full derivative matrices.

    Journal: PLoS ONE

    Article Title: Algorithmic differentiation improves the computational efficiency of OpenSim-based trajectory optimization of human movement

    doi: 10.1371/journal.pone.0217730

    Figure Lengend Snippet: We developed two approaches (AD-ADOLC and AD-Recorder) to make an OpenSim function F and its forward ( F fwd ) and reverse ( F rev ) directional derivatives available within the CasADi environment for use by the NLP solver during the optimization. In the AD-ADOLC approach (top), ADOL-C’s algorithms are used in a C++ code to provide F fwd and F rev . In the AD-Recorder approach (bottom), Recorder provides the expression graph of F as MATLAB source code from which CasADi’s C-code generator generates C-code containing F , F fwd , and F rev . The AD-Recorder approach combines operator overloading, when generating the expression graph, and source code transformation, when processing the expression graph to generate C-code for F , F fwd , and F rev . In both approaches, the code comprising F , F fwd , and F rev is compiled as a Dynamic-link Library (DLL), which is imported as an external function within the CasADi environment. In our application, F represents the multi-body dynamics and is called when formulating the optimal control problem. The latter is then composed into a differentiable optimal control transcription using CasADi. During the optimization, CasADi provides the NLP solver with evaluations of the NLP objective function ( nlp f ), constraints ( nlp g ), objective function gradient ( nlp grad f ), constraint Jacobian ( nlp jac g ), and Hessian of the Lagrangian ( nlp hess l ). CasADi efficiently queries F fwd and F rev to construct the full derivative matrices.

    Article Snippet: First, we enabled the use of AD in OpenSim through a custom source code transformation tool and through the operator overloading tool ADOL-C. Second, we developed an interface between OpenSim and CasADi to solve trajectory optimization problems.

    Techniques: Expressing, Transformation Assay, Control, Construct