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[SKILL] Sync SGLang skill docs (#23921)

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Xiaoyu Zhang
2026-04-28 17:05:36 +08:00
committed by GitHub
parent 71160e4ddb
commit 7824903417
25 changed files with 4199 additions and 1949 deletions
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@@ -66,6 +66,7 @@ Defined in `python/sglang/test/test_utils.py`:
| `stage-b-test-2-gpu-large` | `2-gpu-h100` | Two-GPU correctness and parallelism (TP/PP) on H100 |
| `stage-b-test-4-gpu-b200` | `4-gpu-b200` | Early Blackwell coverage (SM100+ paths) on four GPUs |
| `stage-b-kernel-unit-1-gpu-large` | `1-gpu-h100` | JIT kernel correctness tests under `python/sglang/jit_kernel/tests/` |
| `stage-b-kernel-unit-1-gpu-b200` | `4-gpu-b200` | JIT kernel correctness tests for Blackwell / SM100-specific paths |
| `stage-b-kernel-unit-8-gpu-h200` | `8-gpu-h200` | Multi-GPU JIT kernel correctness tests under `python/sglang/jit_kernel/tests/` |
| `stage-b-kernel-benchmark-1-gpu-large` | `1-gpu-h100` | JIT kernel benchmark files under `python/sglang/jit_kernel/benchmark/` |
| `stage-c-test-4-gpu-h100` | `4-gpu-h100` | Large 4-GPU H100 integration and scaling tests |
@@ -75,7 +76,8 @@ Defined in `python/sglang/test/test_utils.py`:
| `stage-c-test-deepep-8-gpu-h200` | `8-gpu-h200` | DeepEP at 8-GPU H200 scale |
| `stage-c-test-8-gpu-b200` | `8-gpu-b200` | 8-GPU B200 suite (registered but not yet wired to a workflow) |
| `stage-c-test-4-gpu-b200` | `4-gpu-b200` | 4-GPU B200 suite for large models on Blackwell |
| `stage-c-test-4-gpu-gb200` | `4-gpu-gb200` | 4-GPU GB200 suite for large models on Grace Blackwell |
| `stage-c-test-4-gpu-b200-small` | `4-gpu-b200` | Smaller 4-GPU B200 suite split onto low-disk B200 runners |
| `stage-c-test-4-gpu-gb200` | `4-gpu-gb200` | 4-GPU GB200 suite for Grace Blackwell; registered in `run_suite.py`, but the PR workflow is currently disabled until a runner is provisioned |
#### Per-commit (AMD)
@@ -107,7 +109,7 @@ Defined in `python/sglang/test/test_utils.py`:
#### Nightly
Nightly suites are listed in `NIGHTLY_SUITES` in [`test/run_suite.py`](../../../test/run_suite.py). They run via `nightly-test-nvidia.yml`, `nightly-test-amd.yml` amd `nightly-test-npu.yml`, not `pr-test.yml`. Examples:
Nightly suites are listed in `NIGHTLY_SUITES` in [`test/run_suite.py`](../../../test/run_suite.py). They run via `nightly-test-nvidia.yml`, `nightly-test-amd.yml`, and `nightly-test-npu.yml`, not `pr-test.yml`. Examples:
- `nightly-1-gpu` (CUDA)
- `nightly-kernel-1-gpu` (CUDA, JIT kernel full grids)
@@ -132,6 +134,7 @@ Use the lightest suite that meets your test's needs:
- **Most small GPU tests** → `stage-b-test-1-gpu-small` (default choice)
- **Need H100 memory or Hopper features** → `stage-b-test-1-gpu-large`
- **JIT kernel correctness** → `stage-b-kernel-unit-1-gpu-large`
- **JIT kernel correctness for B200 / SM100 paths** → `stage-b-kernel-unit-1-gpu-b200`
- **JIT kernel benchmarks** → `stage-b-kernel-benchmark-1-gpu-large`
- **Multi-GPU** → only when the test actually needs multiple GPUs
@@ -352,6 +355,7 @@ from sglang.test.ci.ci_register import register_cuda_ci
# Correctness tests in python/sglang/jit_kernel/tests/
register_cuda_ci(est_time=30, suite="stage-b-kernel-unit-1-gpu-large")
register_cuda_ci(est_time=30, suite="stage-b-kernel-unit-1-gpu-b200")
register_cuda_ci(est_time=120, suite="stage-b-kernel-unit-8-gpu-h200")
# Benchmarks in python/sglang/jit_kernel/benchmark/