> For the complete documentation index, see [llms.txt](https://summa.gitbook.io/summa/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://summa.gitbook.io/summa/1/backend/summa-aggregation/benchmarks.md). # Benchmarks The following table presents the benchmark results for Summa Aggregation, specifically focused on building the `AggregationMerkleSumTree` as part of the V1 improvements to Summa Solvency. The benchmarks were conducted using an AWS `m7a.8xlarge` main machine with 32 vCores and 128GB RAM, while the workers operated on AWS `c7a.4xlarge` instances with 16 vCores and 32GB RAM. The number of "Chunks" indicates how the 2^20 entries (equivalent to 1,048,576 users) were divided into smaller segments for processing.
-Time for 32 ChunksTime for 64 ChunksTime for 128 Chunks
4 Workers47.166 s47.357 s46.612 s
8 Workers24.262 s23.619 s23.636 s
16 Workers12.378 s12.377 s12.372 s
The benchmark results based on larger entries (2^28) are in the table below:
-Time for 8192 ChunksTime for 16384 Chunks
20 Workers2498 s2469 s
These results indicate that, in most cases, increasing the number of chunks and workers leads to improved performance. This benchmark suggests that custodians can enhance performance by deploying larger machines with additional workers. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://summa.gitbook.io/summa/1/backend/summa-aggregation/benchmarks.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.