Side-by-Side Comparison
adapter vs TritonAscendBench
Compare open source repositories side by side. Stars, forks, code health, licensing, and community growth.
Recorded Stars Comparison
● mtconnect/adapter (99)
● Gxj230958/TritonAscendBench (120)
☆ 99adapter stars
☆ 120TritonAscendBench stars
+21Difference
TritonAscendBenchStar Leader (1.2x)
⚖️ Comparison Verdict
Star Popularity
TritonAscendBench Leads
+21 stars (1.2x ratio)
Forks & Derivatives
adapter Leads
73 total community forks
Recent Maintenance
TritonAscendBench
Pushed 18d ago
Licensing
Different
adapter: — vs TritonAscendBench: Apache-2.0
Side-by-Side Facts
| Metric | mtconnect/adapter ↗ | Gxj230958/TritonAscendBench ↗ |
|---|---|---|
| Description | MTConnect adapter framework | A migration benchmark that measures whether production GPU Triton kernels — extracted from vLLM and SGLang inference paths — can be ported to the Huawei Ascend 910B (Atlas A2) via `triton-ascend` without losing correctness or performance. |
| GitHub Stars | ☆ 99 | ☆ 120 |
| Forks | 73 | 0 |
| Open Issues | 20 | 1 |
| Main Language | C++ | Python |
| License | Not identified | Apache-2.0 |
| Last Push | Aug 14, 2019 | Oct 15, 2026 |
| GitHub Source | Open Source ↗ | Open Source ↗ |
⭐ Embed Verified Badges in README
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adapter Badge
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TritonAscendBench Badge
[](https://githubrepo.cloud/repo/Gxj230958/TritonAscendBench?utm_source=readme_badge)Related Head-to-Head Comparisons
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