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# System prepended metadata

title: 'Dev Update Week 8: Quantifying Precompile Impact in the SP1 zkVM'

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# Dev Update Week 8: Quantifying Precompile Impact in the SP1 zkVM

**Developer:** Developeruche
**Week Ending:** August 8, 2025

### Summary

This week, I moved from a theoretical survey of zkVM precompiles to a rigorous, quantitative analysis. The goal was to measure the real-world performance impact of both **specialized precompiles** and **cryptographic library choice** inside the SP1 zkVM. By benchmarking three different `bn256` libraries (`substrate_bn`, `crypto-bigint`, `arkworks`) across the full proof lifecycle, I have produced definitive data showing that while specialized, high-level precompiles provide the greatest performance boost (up to 7.2x faster proving time), a highly-optimized software library like `arkworks` can, on its own, outperform less-optimized libraries that are only aided by generic, low-level precompiles.


### Accomplishments This Week

* **Comprehensive Benchmarking:** I designed and executed a detailed benchmark comparing six different configurations for `bn256` pairing-based cryptography within SP1. This involved testing three distinct Rust libraries, both with and without precompile support.
* **Execution Performance Analysis:** I measured the raw guest execution cycle counts for each configuration, demonstrating that `arkworks` is by far the most efficient pure-software implementation (2.6x faster than `substrate_bn`) and that SP1's specialized `bn` precompile provides a staggering **27.6x reduction in cycle count**.
* **End-to-End Proving Analysis:** I benchmarked the entire ZK proof lifecycle (proof generation and verification). This crucial step measured the real-world time impact, showing that the `bn` precompile reduced proving time from nearly 5 hours to just **41 minutes**.
* **Quantified Precompile Strategies:** The analysis produced clear data on the tradeoff between specialized ("fat") precompiles and generalized ("bigint") precompiles, proving that accelerating the entire high-level protocol is vastly more effective than only accelerating the underlying arithmetic.


### Key Benchmark Results

This table summarizes the most critical findings from the end-to-end (proving + verification) benchmark.

| Configuration | Library | Precompile | Total Time | Key Finding |
| :--- | :--- | :--- | :--- | :--- |
| `bn-pairing` | `substrate_bn` | None | ~4 hr 58 min | Baseline performance without optimizations is prohibitively slow. |
| `ark-pairing` | `arkworks` | None | **~1 hr 18 min** | **🤯 A superior library alone is 3.8x faster** than the baseline. |
| `bigint-pairing-patched` | `crypto-bigint` | Generic `bigint` | ~3 hr 17 min | A generic precompile helps, but is not transformative. |
| `bn-pairing-patched` | `substrate_bn` | Specialized `bn` | **~41 min 8 sec** | **🏆 A specialized, "fat" precompile is the ultimate performance unlock.** |


### Next Steps & Goals for Next Week

1.  **Publish Findings:** I will consolidate the benchmark methodology, results, and conclusions into a polished technical blog post or research article to share these valuable insights with the broader ZK and Rust developer communities.
2.  **Formalize Precompile Design Proposal:** Using this week's data as evidence, I will finalize the "Minimal Standard" precompile proposal I started in Week 7. The data strongly supports prioritizing a smaller set of high-level, specialized precompiles over a wide array of generic ones.
3.  **Investigate `arkworks` Optimizations:** I will conduct a brief code review of the `arkworks` `bn254` implementation to understand the specific algorithmic optimizations that make it so performant in a pure-software context.
4.  **Explore Other Cryptographic Primitives:** I will scope out a similar, smaller-scale benchmark for another critical primitive, such as `Keccak256` or `SHA-256`, to see if the same patterns of library performance and precompile impact hold true.


### Challenges & Learnings

* **Challenge: Long Proving Times:** The multi-hour proving times for non-optimized configurations made for a slow and resource-intensive feedback loop. This underscores the critical importance of performance optimization for developer experience.
* **Learning 1: Not All Precompiles Are Created Equal:** The most profound insight is the massive difference between a generic `bigint` precompile and a specialized `bn` precompile. Accelerating low-level math is helpful, but accelerating the entire high-level protocol is a game-changer. This has major implications for future zkVM design.
* **Learning 2: Software Optimization Can Outweigh Generic Hardware Acceleration:** The fact that `arkworks` *without* a precompile outperformed another library *with* a generic precompile is a powerful lesson. It proves that high-quality, algorithmically-sound software is just as important as hardware acceleration.
* **Learning 3: The Path to Practicality:** This benchmark provided a clear, data-backed roadmap to making complex cryptography practical inside a zkVM. The combination of a specialized precompile and a well-written library is what moves ZK applications from theoretical curiosities to usable tools.