[Perf] Linux/x64: 1 Improvement on 6/23/2026 2:47:31 AM +00:00

### Run Information

Name | Value
-- | --
Architecture | x64
OS | ubuntu 22.04
Queue | ViperUbuntu
Baseline | [fc23f447cfbddb07670e92dab98c794f0499d406](https://github.com/dotnet/runtime/commit/fc23f447cfbddb07670e92dab98c794f0499d406)
Compare | [461fd2adbf736b4298d9a0c58ad8dbcecaf83629](https://github.com/dotnet/runtime/commit/461fd2adbf736b4298d9a0c58ad8dbcecaf83629)
Diff | [Diff](https://github.com/dotnet/runtime/compare/fc23f447cfbddb07670e92dab98c794f0499d406...461fd2adbf736b4298d9a0c58ad8dbcecaf83629)
Configs | CompilationMode:tiered, RunKind:micro

### Improvements in System.Buffers.Binary.Tests.BinaryReadAndWriteTests

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

• [MeasureReverseUsingNtoH - 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 'System.Buffers.Binary.Tests.BinaryReadAndWriteTests*'
```

### System.Buffers.Binary.Tests.BinaryReadAndWriteTests.MeasureReverseUsingNtoH

#### 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 the linked benchmark source, src/benchmarks/micro/libraries/System.Buffers/BinaryReadAndWriteTests.cs lines 197-209, and compare the baseline and test reports for MeasureReverseUsingNtoH. Run the supplied benchmarks_ci.py command using the Linux/x64 configuration. Done is not defined by the issue; first determine whether the reported improvement is reproducible and actionable.

Written by the indexing model from the issue text.