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_posts/2024-10-17-improving-performance-of-biodynamo-using-cpp-modules.md
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title: "Wrapping up GSoC'24: Improving performance of BioDynaMo using ROOT C++ Modules" | ||
layout: post | ||
excerpt: "This project, part of Google Summer of Code 2024, aims to reduce the header parsing in BioDynaMo using the ROOT C++ Modules" | ||
sitemap: false | ||
author: Isaac Morales Santana | ||
permalink: blogs/gsoc24_isaac_morales_wrapup_blog/ | ||
banner_image: /images/blog/gsoc-banner.png | ||
date: 2024-10-17 | ||
tags: gsoc root cmake c++ | ||
--- | ||
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### Introduction | ||
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I am Isaac Morales, a Computer Engineering student at the University of Granada, Spain. | ||
This summer I had the opportunity to participate in Google Summer of Code 2024. My project | ||
revolved around enhancing BioDynaMo's performance using the ROOT C++ Modules. | ||
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**Mentors**: Vassil Vassilev, Lukas Breitwieser. | ||
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### Project overview | ||
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BioDynaMo is an agent-based simulation platform designed to facilitate complex simulations, | ||
particularly in fields like cancer research, epidemiology, and social sciences. It leverages | ||
ROOT—a framework widely used in high-energy physics—for statistical analysis, random number | ||
generation, C++ Jupyter notebooks, and I/O operations. However, enhancing BioDynaMo’s performance | ||
remains a key challenge. This is where this Google Summer of Code 2024 (GSoC ‘24) project comes | ||
into play, focusing on optimizing the platform through ROOT C++ Modules. | ||
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### The Challenge: Performance Bottlenecks in BioDynaMo | ||
BioDynaMo’s reflection system, which utilizes Cling (an interactive C++ interpreter from ROOT), | ||
experiences significant runtime performance and memory usage issues. The repeated parsing of library | ||
descriptors by Cling introduces inefficiencies that slow down the startup phase and consume excessive | ||
memory. These bottlenecks are especially evident in simulations with a low number of time steps, as | ||
a substantial portion of the time is spent on parsing rather than on actual computations. | ||
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### The Solution: Integrating ROOT C++ Modules. | ||
The primary goal of the GSoC project was to integrate ROOT’s C++ Modules into BioDynaMo to minimize | ||
these performance issues. C++ Modules offer an efficient on-disk representation of C++ code, | ||
reducing the need for repeated parsing of invariant code. By implementing these modules, | ||
the project aimed to optimize runtime memory usage and improve overall performance | ||
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## Key steps undertaken include: | ||
1. **Reworking CMake Rules:** The project incorporated ROOT and another packages | ||
efficiently using FetchContent, modifying CMake rules accordingly (e.g., PR [#365](https://github.com/BioDynaMo/biodynamo/pull/365) | ||
and [#387](https://github.com/BioDynaMo/biodynamo/pull/387)) | ||
2. **Replacing genreflex with rootcling:** This switch was crucial to enable C++ Modules and | ||
streamline the generation of reflection information (PR [#379](https://github.com/BioDynaMo/biodynamo/pull/379)) | ||
3. **Automatic Modules Map Generation:** Using relative paths, the CMake system was modified to | ||
automate module map creation, ensuring smooth integration with BioDynaMo's libraries. | ||
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### Promising Results | ||
The results have been promising, showcasing significant performance gains. Benchmarking revealed | ||
improvements ranging from 18% reduction in peak memory usage with the default modules.idx to 25% with the | ||
updated one. | ||
![Plot of the peak memory usage in various demos](/images/blog/bdm-peak-memory.png) | ||
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Moreover, the startup phase saw an impressive 80% reduction in time, thanks to the optimized | ||
handling of header parsing. That highlights the efficiency of C++ Modules in minimizing | ||
Cling’s parsing overhead | ||
![Plot of the startup time in various demos](/images/blog/bdm-startup-time.png) | ||
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As expected, the simulation time did not show an appreciable improvement. However, in the | ||
unit tests, the time was 33% lower. I believe this is because unit tests involve a lot of parsing and Cling calls. | ||
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### Future Steps and Challenges Ahead | ||
Despite these advances, several challenges remain. For instance, memory leaks have been observed when using the new | ||
`ROOT_GENERATE_DICTIONARY`, even with C++ Modules disabled. Additionally, the build system for individual demos has | ||
caused compatibility issues with the main build system. Resolving these issues and finalizing the integration of C++ | ||
Modules will be essential for ensuring long-term stability and reliability. | ||
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Looking ahead, further optimizations are planned, including potential module-based optimizations for BioDynaMo’s | ||
core components. Collaboration with the BioDynaMo team continues, with upcoming meetings scheduled | ||
to align efforts and resolve outstanding issues. | ||
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### Conclusion | ||
The integration of C++ Modules has proven effective in reducing memory usage and startup time, although some hurdles remain. | ||
Continued collaboration and testing will be crucial to fully realize the performance potential of BioDynaMo, | ||
enabling more efficient simulations for researchers in computational biology. | ||
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### Related Links | ||
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- [ROOT website](https://root.cern) | ||
- [BioDynaMo website](https://www.biodynamo.org/) | ||
- [My GitHub Profile](https://github.com/imorlxs) | ||
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