[Perf] Linux/x64: 1 Improvement on 9/3/2026 3:04:34 PM +00:00

### Run Information

Name | Value
-- | --
Architecture | x64
OS | ubuntu 22.04
Queue | ViperUbuntu
Baseline | [147c024e64965dd98d68ed8419e4f5320852e8ca](https://github.com/dotnet/sdk/commit/147c024e64965dd98d68ed8419e4f5320852e8ca)
Compare | [1fee94ef34a9c6e2e4cf4199d9a546ef8a2a927d](https://github.com/dotnet/sdk/commit/1fee94ef34a9c6e2e4cf4199d9a546ef8a2a927d)
Diff | [Diff](https://github.com/dotnet/sdk/compare/147c024e64965dd98d68ed8419e4f5320852e8ca...1fee94ef34a9c6e2e4cf4199d9a546ef8a2a927d)
Configs | CompilationMode:tiered, RunKind:akadeindexedset

### Improvements in Akade.IndexedSet.Benchmarks.RealWorld.EventSourcedAggregateCache.QueryBenchmarks

Benchmark | Baseline | Test | Test/Base | Test Quality | Edge Detector | Baseline IR | Compare IR | IR Ratio
-- | -- | -- | -- | -- | -- | -- | -- | --
|

• [GetViaPrimaryId - Duration of single invocation]()
• 📝 - [Benchmark Source]()
• [ADX - Test Multi Config Graph]()

![graph]()
[Test Report]()

### Repro
General Docs link: https://github.com/dotnet/performance/blob/main/docs/benchmarking-workflow-dotnet-runtime.md

```cmd
git clone https://github.com/dotnet/performance.git
python3 .\performance\scripts\benchmarks_ci.py -f net8.0 --filter 'Akade.IndexedSet.Benchmarks.RealWorld.EventSourcedAggregateCache.QueryBenchmarks*'
```

### Akade.IndexedSet.Benchmarks.RealWorld.EventSourcedAggregateCache.QueryBenchmarks.GetViaPrimaryId

#### ETL Files

#### Histogram

#### JIT Disasms

### Docs

[Profiling workflow for dotnet/runtime repository](https://github.com/dotnet/performance/blob/master/docs/profiling-workflow-dotnet-runtime.md)
[Benchmarking workflow for dotnet/runtime repository](https://github.com/dotnet/performance/blob/master/docs/benchmarking-workflow-dotnet-runtime.md)

Start with src/benchmarks/real-world/Akade.IndexedSet.Benchmarks/RealWorld/EventSourcedAggregateCache/QueryBenchmarks.cs, especially GetViaPrimaryId, and read the benchmarking workflow documentation. Reproduce the reported run with scripts/benchmarks_ci.py and the supplied filter, then compare the benchmark report with the baseline. Done requires determining whether the measured improvement needs follow-up and recording the result.

Written by the indexing model from the issue text.