Analyses of a model-based real-time language embedded in C++

Prastowo, Tadeus; Palopoli, Luigi; Abeni, Luca; Lipari, Giuseppe

doi:10.1145/3341105.3373994

Cited by 2 publications

(2 citation statements)

References 24 publications

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“…To conclude, while Figure 21 has been analyzed with the conclusions that the compilation times of Tice models that are similar to the ones evaluated in this section would be reasonable in practice, the Tice models evaluated in Figure 21 have their Criterion 6 capped at 200 times by modifying the actual periods and interarrival times actually used in the WATERS 2017 Industrial Challenge, which are shown in Table 3. In other words, the actual periods and interarrival times used in the WATERS 2017 Industrial Challenge have shown that the internals of Tice library 41 should be further improved, in particular by using different techniques to decrease its memory consumption when analyzing temporal constraints, for example, by implementing the analyses using constexpr‐function iterations instead of class‐template recursions.…”

Section: The Compilation Times Of Tice Programsmentioning

confidence: 99%

Tice: A real‐time language compilable using C++ compilers

2020

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Summary Model‐based development (MBD) holds the promise to capture potential timing problems in embedded software during the early phases of the development, securing the production of bug‐free embedded software. For most MBD approaches, the source code is just an intermediate artifact that can be generated automatically from the models. This assumption clashes with an undeniable fact: a large share of the commercial embedded software exploits existing libraries or is developed using C/C++ natively. A way to reconcile the ambitions of MBD with the use of a programming language is by offering new language constructs and an innovative compilation tool‐chain that prevents model error and timing problems “by construction.” However, the persistent popularity of C/C++ among embedded programmers and the limited availability of tools have severely limited the uptake of alternative programming languages for embedded software. Therefore, we propose an original route. Our language proposal, named Tice, has been shaped as a C++ active library. Tice retains full compatibility with existing C++ code, which can be integrated easily into new Tice‐based projects. The enforcement of Tice syntax and semantics can be made by a standard C++ compiler, forgoing the need for new tools. In this article, we describe Tice's syntax, semantics, and model of computation and communication. We demonstrate Tice's practical applicability on an industrial scale use‐case and give ample evidence for Tice's efficient compilation using off‐the‐shelf C++ compilers. Finally, we show Tice's code generation process.

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Section: The Compilation Times Of Tice Programsmentioning

confidence: 99%

Tice: A real‐time language compilable using C++ compilers

2020

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“…The readability and extensive range of scientific computing libraries, such as TensorFlow and PyTorch, or using integrated development environment tools make it a popular choice for investigating diverse quality control methods for different petroleum products [22,23]. Speed and control over hardware resources are crucial in real-time production environments, C/C++ are utilized in this context [24]. They excel in installing models for fast analysis and low latency, enabling immediate alterations in quality control procedures, but needing additional development experience [25].…”

Section: Introductionmentioning

confidence: 99%

An attempt to promote intelligent petroleum processing: a look at how different programming languages works with deep learning models for gasoline quality detection

Alzahawi,

Issa

2024

Preprint

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The current study explores how several programming languages affect deep learning models for gasoline quality detection, highlighting the significance of choosing the best appropriate language according to project needs. Featuring several scientific computations using an integrated development environment of the Visual Studio Code (VS Code) tool. This work has reached multiple outcomes: Python is known for its rapid development and adaptability, which are well-suited for exploring quality control techniques in petroleum products. Java is recognized for its stability and flexibility to work across many platforms, making it ideal for large-scale deployments that require dependable performance in refinery equipment. C/C++ is lauded for its speed and ability to manage hardware resources effectively, which is essential in real-time production settings, allowing for quick analysis and little delay in quality control processes. The study utilizes a deep learning architecture in Java, C, and Python, with frameworks such as Visual Studio Code to aid in model construction, with the goal of creating flexible tools for monitoring the dynamic quality of petroleum products.

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Analyses of a model-based real-time language embedded in C++

Cited by 2 publications

References 24 publications

Tice: A real‐time language compilable using C++ compilers

Tice: A real‐time language compilable using C++ compilers

An attempt to promote intelligent petroleum processing: a look at how different programming languages works with deep learning models for gasoline quality detection

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