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# <imgsrc="doc/source/img/DTLMod_logo.png"alt="DTLMod Logo"width="60"style="vertical-align: middle; margin-right:12px;"> DTLMod: a versatile simulated Data Transport Layer
# <imgsrc="doc/source/img/DTLMod_logo.png"width="60"style="vertical-align: middle; margin-right:12px;"> DTLMod: a versatile simulated Data Transport Layer
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## What is DTLMod?
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DTLMod is a high-performance simulation library that provides realistic data transport layer modeling for distributed systems. Built on top of [SimGrid](https://simgrid.org), it enables researchers and developers to accurately simulate complex data movement patterns in HPC workflows, in-situ processing, and distributed computing scenarios without the cost and complexity of physical infrastructure.
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### Key Features
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- 🚀 **High-fidelity simulation** of data transport protocols
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- 🔧 **Flexible API** for easy integration into SimGrid-based simulators
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- 📊 **Performance modeling** for in-situ workflows and data movement
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- ✅ **Well-tested** with comprehensive unit test coverage
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- 📖 **Extensively documented** with examples and API reference
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### Use Cases
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- Evaluating in-situ workflow performance
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- Modeling data-intensive scientific applications
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- Testing distributed system architectures
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- Optimizing data placement and movement strategies
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## Table of Contents
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-[What is DTLMod?](#what-is-dtlmod)
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-[📖 Documentation](#-documentation)
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-[🛠️ Dependencies and Installation](#️-dependencies-and-installation)
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-[🤝 Contributing](#-contributing)
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-[💬 Support](#-support)
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-[📝 Citation](#-citation)
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## 📖 Documentation
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The complete documentation is available at [simgrid.github.io/DTLMod](https://simgrid.github.io/DTLMod/), including:
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### User Manual
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-**Getting Started**: Installation and project setup
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-**Workflow Design**: Creating simulated in-situ processing workflows with the programming interface
The only required dependencies are on [SimGrid](https://simgrid.frama.io/simgrid/) and its
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[File System Module](https://github.com/simgrid/file-system-module). An optional dependency
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is [Google Test](https://github.com/google/googletest) for compiling the unit tests.
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-[Google Test](https://github.com/google/googletest) (for C++ unit tests)
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-[Python 3](https://www.python.org/) and [pybind11](https://github.com/pybind/pybind11) 2.4+ (for Python bindings)
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Here is the typical Ubuntu installation procedure:
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### Building and Installing
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Here is the typical installation procedure:
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```bash
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cdDTL
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cdDTLMod
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mkdir build
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cd build
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cmake ..
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make -j4
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sudo make install
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```
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after which the dtlmod library and header files will be installed in `/usr/local/`.
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The dtlmod library and header files will be installed in `/usr/local/`.
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### Running Tests
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To compile and run the unit tests, just run the following command in the `build` directory:
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**C++ unit tests:**
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```bash
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# From the build directory
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make unit_tests
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./unit_tests
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```
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## Citation
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**Python unit tests:**
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```bash
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# From the build directory
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cd test/python
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python ./unit_tests_python.py
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```
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## 🤝 Contributing
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Contributions are welcome! Here's how you can help:
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-**Report bugs**: Open an issue on the [GitHub issue tracker](https://github.com/simgrid/DTLMod/issues)
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-**Submit pull requests**: Fork the repository, make your changes, and submit a PR
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-**Improve documentation**: Help us improve examples and API documentation
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-**Share use cases**: Let us know how you're using DTLMod in your research
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Please ensure your code follows the existing style and includes appropriate tests.
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## 💬 Support
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If you need help or have questions:
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-**Documentation**: Check the [complete documentation](https://simgrid.github.io/DTLMod/) first
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-**Issues**: Search existing [GitHub issues](https://github.com/simgrid/DTLMod/issues) or open a new one
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-**SimGrid Community**: For general SimGrid questions, visit [simgrid.org](https://simgrid.org/)
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## 📝 Citation
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If you use this software in your research, please cite:
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```bibtex
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@inproceedings{dtlmod,
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title = {{A Versatile Simulated Data Transport Layer for In Situ
@@ -59,7 +141,8 @@ If you use this software in your research, please cite:
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}
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```
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This article comes with a complete experimental artifact that can be
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found on [figshare](https://doi.org/10.6084/m9.figshare.28872509.v1).
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### Reproducibility Artifact
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The complete experimental artifact for this paper, including all datasets, scripts, and instructions for reproducing the results, is available on [figshare](https://doi.org/10.6084/m9.figshare.28872509.v1).
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