[Perf] Linux/arm64: 1 Improvement on 8/12/2026 5:14:24 AM +00:00

### Run Information

Name | Value
-- | --
Architecture | arm64
OS | azurelinux 3.0
Queue | CobaltAzureLinux
Baseline | [1fdccbc9c3690a80a9579bdc0e9be997db1ac0de](https://github.com/dotnet/runtime/commit/1fdccbc9c3690a80a9579bdc0e9be997db1ac0de)
Compare | [e8c760f0bfa9ecd023c4d99bd5a4460da8f60653](https://github.com/dotnet/runtime/commit/e8c760f0bfa9ecd023c4d99bd5a4460da8f60653)
Diff | [Diff](https://github.com/dotnet/runtime/compare/1fdccbc9c3690a80a9579bdc0e9be997db1ac0de...e8c760f0bfa9ecd023c4d99bd5a4460da8f60653)
Configs | CompilationMode:tiered, RunKind:micro

### Improvements in System.Buffers.Tests.RentReturnArrayPoolTests<Byte>

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

• [SingleSerial - 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
py .\performance\scripts\benchmarks_ci.py -f net8.0 --filter 'System.Buffers.Tests.RentReturnArrayPoolTests*'
```

### System.Buffers.Tests.RentReturnArrayPoolTests<Byte>.SingleSerial(RentalSize: 4096, ManipulateArray: False, Async: True, UseSharedPool: False)

#### 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/micro/libraries/System.Buffers/ArrayPoolTests.cs#L48-L60 and run the provided benchmarks_ci.py filter for RentReturnArrayPoolTests. Review the linked ARM64 AzureLinux comparison and test reports to determine whether the improvement is reproducible and actionable; done means a documented finding or validated change.

Written by the indexing model from the issue text.