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The bridge codebase contains CPU-heavy code which is prone to becoming a bottleneck for async applications. Such tasks include signing, transaction generation, key aggregation, elliptic curve calculations.
Issue #385 highlighted a potential path forward for performance optimizations, but to determine the impact of performance optimizations, we first need a way to collect data on our current performance. This is done through benchmarks, as outlined in The Rust Performance Book.
A benchmark suite will enable us to track the performance impact of changes and avoid regressions. It will provide us a baseline for improvement and give us a better understanding of the areas that have the biggest impact on performance.
This issue tracks the implementation of a benchmarking suite that measures significant codepaths. The integration of such benchmarks into PR regression tracking will be tracked in a future issue.
Proposal Description
The bridge codebase contains CPU-heavy code which is prone to becoming a bottleneck for async applications. Such tasks include signing, transaction generation, key aggregation, elliptic curve calculations.
Issue #385 highlighted a potential path forward for performance optimizations, but to determine the impact of performance optimizations, we first need a way to collect data on our current performance. This is done through benchmarks, as outlined in The Rust Performance Book.
A benchmark suite will enable us to track the performance impact of changes and avoid regressions. It will provide us a baseline for improvement and give us a better understanding of the areas that have the biggest impact on performance.
This issue tracks the implementation of a benchmarking suite that measures significant codepaths. The integration of such benchmarks into PR regression tracking will be tracked in a future issue.
Related to #385
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