dotnet / dotnet/perf-autofiling-issues

[Perf] Linux/x64: 2 Improvements on 4/3/2026 3:30:25 AM -07:00

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arch-x64 branch-refs/heads/main compilationmode-tiered kind-micro os-linux perf-improvement runkind-micro runtime-coreclr untriaged
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Description

### Run Information

Name | Value
-- | --
Architecture | x64
OS | ubuntu 22.04
Queue | ViperUbuntu
Baseline | [e0214a72b62cc3518fd6551b7af7ed630cb380f4](https://github.com/dotnet/runtime/commit/e0214a72b62cc3518fd6551b7af7ed630cb380f4)
Compare | [d5dc74a6f182eeece827d42d12c59ac3311d59af](https://github.com/dotnet/runtime/commit/d5dc74a6f182eeece827d42d12c59ac3311d59af)
Diff | [Diff](https://github.com/dotnet/runtime/compare/e0214a72b62cc3518fd6551b7af7ed630cb380f4...d5dc74a6f182eeece827d42d12c59ac3311d59af)
Configs | CompilationMode:tiered, RunKind:micro

### Improvements in System.Numerics.Tensors.Tests.Perf_NumberTensorPrimitives<Int32>

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

  • [BitwiseAnd_Vector - Duration of single invocation]()
  • 📝 - [Benchmark Source]()
  • [ADX - Test Multi Config Graph]()
| 419.88 ns | 12.71 ns | 0.03 | 0.44 | False | | |

[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.Numerics.Tensors.Tests.Perf_NumberTensorPrimitives*'
```

### System.Numerics.Tensors.Tests.Perf_NumberTensorPrimitives<Int32>.BitwiseAnd_Vector(BufferLength: 128)

#### 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)

---

### Run Information

Name | Value
-- | --
Architecture | x64
OS | ubuntu 22.04
Queue | ViperUbuntu
Baseline | [e0214a72b62cc3518fd6551b7af7ed630cb380f4](https://github.com/dotnet/runtime/commit/e0214a72b62cc3518fd6551b7af7ed630cb380f4)
Compare | [d5dc74a6f182eeece827d42d12c59ac3311d59af](https://github.com/dotnet/runtime/commit/d5dc74a6f182eeece827d42d12c59ac3311d59af)
Diff | [Diff](https://github.com/dotnet/runtime/compare/e0214a72b62cc3518fd6551b7af7ed630cb380f4...d5dc74a6f182eeece827d42d12c59ac3311d59af)
Configs | CompilationMode:tiered, RunKind:micro

### Improvements in System.Numerics.Tensors.Tests.Perf_NumberTensorPrimitives<Single>

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

  • [MaxMagnitude_Vector - Duration of single invocation]()
  • 📝 - [Benchmark Source]()
  • [ADX - Test Multi Config Graph]()
| 434.42 ns | 10.42 ns | 0.02 | 0.39 | False | | |

[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.Numerics.Tensors.Tests.Perf_NumberTensorPrimitives*'
```

### System.Numerics.Tensors.Tests.Perf_NumberTensorPrimitives<Single>.MaxMagnitude_Vector(BufferLength: 128)

#### 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)

Contributor guide

No contributing guide indexed for this repository

Research direction

Start with src/benchmarks/micro/libraries/System.Numerics.Tensors/Perf_NumberTensorPrimitives.cs at the cited BitwiseAnd_Vector and MaxMagnitude_Vector benchmarks. Run the listed benchmarks using scripts/benchmarks_ci.py and inspect the linked performance and IR reports to determine whether the improvements are reproducible and actionable. Done means documenting the cause and an appropriate runtime or benchmark follow-up.

Written by the indexing model from the issue text.

Assessment

Tech stack
csharp
Domain
performance
Issue type
Bug
Difficulty
4/5
Estimated time
3-5 days
Activity status
Quiet
Clarity
Needs clarification
Newbie friendliness
35/100

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