# Searching for RH Counterexamples -- Scaling Up

DevFeed: [Searching for RH Counterexamples -- Scaling Up](<https://devfeed.tech/articles/searching-for-rh-counterexamples-scaling-up-40444.md>)

Original publisher: [Read original article](<https://www.jeremykun.com/2021/02/16/searching-for-rh-counterexamples-scaling-up/>)

Published: 2021-02-16T09:00:00Z

Content type: article

Language: en

Sources: [Jeremy Kun](<https://devfeed.tech/sources/jeremy-kun.md>)

Topics: [Mathematics](<https://devfeed.tech/topics/mathematics.md>), [hashing](<https://devfeed.tech/topics/hashing.md>), [scaling](<https://devfeed.tech/topics/scaling.md>), [sha256](<https://devfeed.tech/topics/sha256.md>), [hash](<https://devfeed.tech/topics/hash.md>), [Database](<https://devfeed.tech/topics/database.md>)

Tags: [architecture](<https://devfeed.tech/tags/architecture.md>), [disk-space](<https://devfeed.tech/tags/disk-space.md>), [hashing](<https://devfeed.tech/tags/hashing.md>), [mathematics](<https://devfeed.tech/tags/mathematics.md>), [performance](<https://devfeed.tech/tags/performance.md>), [postgres](<https://devfeed.tech/tags/postgres.md>), [programming](<https://devfeed.tech/tags/programming.md>), [refactor](<https://devfeed.tech/tags/refactor.md>), [riemann-hypothesis](<https://devfeed.tech/tags/riemann-hypothesis.md>), [scaling](<https://devfeed.tech/tags/scaling.md>), [sha256](<https://devfeed.tech/tags/sha256.md>), [software](<https://devfeed.tech/tags/software.md>)

## AI overview

This article describes scaling a search for counterexamples to the Riemann Hypothesis. It focuses on reducing storage by keeping deterministic SHA-256 summaries instead of every witness value and refactoring the application into a worker architecture.

## Source excerpt

We're ironically searching for counterexamples to the Riemann Hypothesis. Setting up Pytest Adding a Database Search Strategies Unbounded integers Deploying with Docker Performance Profiling Last time we made the audacious choice to remove primary keys from the RiemannDivisorSums table for performance reasons. To help with that, we will do two things in this post Reduce the storage footprint of the whole application (it was 60 GiB when it crashed, and we got up to 84 prime factors).