dotnet / dotnet/perf-autofiling-issues
[Perf] Linux/x64: 1 Regression on 7/1/2026 8:54:35 AM +00:00
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Description
### Run Information
Name | Value
-- | --
Architecture | x64
OS | ubuntu 22.04
Queue | ViperUbuntu
Baseline | [3e328deefbd3029c2f957050c508b4faeee3d71f](https://github.com/dotnet/sdk/commit/3e328deefbd3029c2f957050c508b4faeee3d71f)
Compare | [a9679a8de87742e170318ea39f7f0e2874bcd441](https://github.com/dotnet/sdk/commit/a9679a8de87742e170318ea39f7f0e2874bcd441)
Diff | [Diff](https://github.com/dotnet/sdk/compare/3e328deefbd3029c2f957050c508b4faeee3d71f...a9679a8de87742e170318ea39f7f0e2874bcd441)
Configs | CompilationMode:tiered, RunKind:imagesharp
### Regressions in SixLabors.ImageSharp.Benchmarks.Codecs.EncodeTga
Benchmark | Baseline | Test | Test/Base | Test Quality | Edge Detector | Baseline IR | Compare IR | IR Ratio
-- | -- | -- | -- | -- | -- | -- | -- | --
|
- [ImageSharpTga - 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 'SixLabors.ImageSharp.Benchmarks.Codecs.EncodeTga*'
```
### SixLabors.ImageSharp.Benchmarks.Codecs.EncodeTga.ImageSharpTga(TestImage: "Tga/targa_24bit.tga")
#### 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 the benchmark source at src/benchmarks/real-world/ImageSharp/Codecs/EncodeTga.cs#L40-L45 and compare the Baseline and Compare commits linked in the issue. Run the provided benchmarks_ci.py command for the EncodeTga filter, then use the linked test report and profiling workflow to investigate the regression. Done means identifying and addressing the cause of the 10% slowdown.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- csharp, linux, python, ubuntu
- Domain
- operating-systems, performance, testing-qa
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Quiet
- Clarity
- Needs clarification
- Newbie friendliness
- 30/100