Add blog and fix poster

_data/preslist.yml

@@ -1,13 +1,13 @@
 - title: "Improving BioDynamo's Performance using ROOT C++ Modules"
   description: |
-    Poster presented at the FOURTH Mode Workshop on Differentiable Programming for Experiment Desing
+    Poster presented at the FOURTH Mode Workshop on Differentiable Programming for Experiment Design
   location: "[Fourth MODE Workshop](https://indico.cern.ch/event/1380163/)"
   date: 2024-09-24
   speaker: Isaac Morales Santana
   id: "FOURTHMODEBDM"
   artifacts: |
     [Link to poster](/assets/presentations/Fourth_MODE_Isaac_Morales.pdf)
-  highlight: 1
+  highlight: 0
 
 - title: "Accelerating Large Scientific Workflows Using Source Transformation Automatic Differentiation"
   description: |

_posts/2024-10-17-improving-performance-of-biodynamo-using-cpp-modules.md

@@ -0,0 +1,104 @@
+---
+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++ 
+---
+
+### Introduction
+
+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.
+
+**Mentors**: Vassil Vassilev, Lukas Breitwieser.
+
+
+### Project overview
+
+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.
+
+### 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.
+
+### 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
+
+## What I did?:
+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), both merged)
+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. **C++ Modules changes** Among other things, I used automatic generation for the module map with relative paths,
+modified the `selection.xml` file to support the new dictionaries and fixed headers with missing includes (PR [#385](https://github.com/BioDynaMo/biodynamo/pull/385).
+4. **Updated some CI workflows** I fixed some failing workflows in PR [#377](https://github.com/BioDynaMo/biodynamo/pull/377).
+Also, I did some minor changes in some flags in PR's [#378](https://github.com/BioDynaMo/biodynamo/pull/378) and [#367](https://github.com/BioDynaMo/biodynamo/pull/367)
+
+### 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)
+
+
+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)
+
+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.
+
+### Future Steps and Challenges Ahead
+Despite these advances, several challenges remain. PR's #365 is ready to merge and #385 needs some changes. 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. Also, there is a problem with the Jupyter notebooks.
+Resolving these issues and finalizing the integration of C++ Modules will be essential for ensuring long-term stability and reliability.
+
+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.
+
+### 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.
+
+### Acknowledges
+First of all, I would like to thank Google Summer of Code for the opportunity to work on this project.
+But above all, my most sincere gratitude goes to Vassil. He has been an exceptional mentor, always attentive
+and ready to help with anything I needed. His encouragement during weekly meetings and his constant support in all areas,
+from soft skills to technical expertise, have truly inspired me and earned my admiration.
+
+Many thanks also to the BioDynaMo team: to Lukas Breitweiser for guiding me through the final stages and helping
+me understand the complexities of BioDynaMo; to Tobias Duswald for reviewing my PRs and assisting me in analyzing
+my results; and to Fons Rademakers for his support when I faced challenges compiling ROOT in debug mode.
+
+Lastly, a special thanks to my colleagues from Compiler Research, particularly David, Attel and Maksym, whom I had
+the pleasure of meeting at the Fourth MODE in Valencia, for making this experience unforgettable.
+
+### Related Links
+
+- [ROOT website](https://root.cern)
+- [BioDynaMo website](https://www.biodynamo.org/)
+- [My GitHub Profile](https://github.com/imorlxs)
+
+