---
# System prepended metadata

title: 'Dev Update Week 10: Finalizing and Submitting Precompile Research'

---

# Dev Update Week 10: Finalizing and Submitting Precompile Research

**Developer:** Developeruche
**Week Ending:** August 23, 2025

### Summary

The past two weeks were dedicated to synthesizing the extensive benchmark data from previous weeks into a comprehensive technical report. The primary focus was to articulate a clear, data-backed argument on the "Fat vs. Lean Precompile" debate. This effort culminated in a completed draft report, which has now been submitted to my mentor for review and feedback. The report's core thesis advocates for the long-term sustainability and interoperability of "lean" precompiles, despite the undeniable short-term speed advantage of specialized "fat" precompiles.

### Accomplishments This Week

* **Completed Draft Report:** I finalized the technical report titled, **"Fat vs. Lean Precompiles in zkVMs: Short-Term Speed or Long-Term Sustainability?"**. This document consolidates all the benchmark data, analysis, and key conclusions from the `bn256` performance investigation in the SP1 zkVM.
* **Submitted for Mentor Review:** The completed draft has been shared with my mentor. The goal is to receive critical feedback on the analysis, the structure of the argument, and the clarity of the conclusions before any public release.
* **Distilled Core Argument:** The writing process helped distill the research into a clear takeaway: While "fat" precompiles offer a massive **~7x proving speedup**, they risk ecosystem fragmentation. In contrast, "lean" precompiles, especially when paired with highly-optimized libraries like `arkworks`, provide a more sustainable path, delivering significant (**up to 4x**) performance gains without sacrificing modularity or long-term maintainability.

### Next Steps & Goals for Next Week

1.  **Incorporate Mentor Feedback:** The immediate priority is to receive and thoroughly incorporate the feedback from my mentor to strengthen the report's arguments and improve its overall quality.
2.  **Prepare for Public Release:** Based on the feedback, I will begin editing the draft into a polished, public-facing format, such as a blog post or technical article, to share the findings with the community.
3.  **Begin Scoping `Keccak256` Benchmark:** While awaiting feedback, I will start the preliminary research for the next performance analysis, focusing on the `Keccak256` hashing function. This will involve identifying suitable Rust libraries and designing a relevant guest program.
4.  **Archive and Document Benchmark Code:** I will clean up, comment, and add a comprehensive `README` to the `bn256` benchmark repository to ensure the work is well-documented and reproducible.

### Challenges & Learnings

* **Challenge: From Data to Narrative:** The primary challenge was transitioning from raw benchmark data to a compelling and coherent written narrative. It required carefully structuring the argument to guide the reader through the evidence and lead them to a logical conclusion about the precompile trade-offs.
* **Learning: The Importance of Framing:** I learned that how you frame the data is as important as the data itself. Presenting the results not just as a "winner vs. loser" comparison, but as a strategic choice between "short-term speed" and "long-term sustainability," makes the findings much more impactful and relevant to ongoing zkVM design discussions.
* **Learning: Writing Solidifies Understanding:** The process of writing the report and defending its conclusions forced me to deeply scrutinize my own assumptions and analysis. It was a critical step in solidifying my understanding of the nuanced performance dynamics within the zkVM.