Files
sglang/test/registered/unit
leavelet dbc5ebbaa0 CP HiCache: multi-slab host KV cache to respect cudaHostRegister per-call ceiling
A single cudaHostRegister over a >~1 TB host buffer fails with
cudaErrorMemoryAllocation on B300 (hard per-call ceiling: 512 GiB OK, 1024 GiB
FAIL), crashing the hicache_size=1600 (~1.5 TB CP shared-L2 slab) prefill at
startup. The registration cannot simply be chunked: a memcpy (cudaMemcpyBatchAsync,
the CP-L2 H2D/D2H transfer) fails with cudaErrorInvalidValue when its host range
straddles a registration boundary (verified empirically on b300-049).

Fix: physically split the host cache into multiple page-aligned slabs, each <= a
safe single-registration size (default 480 GiB, env SGLANG_CP_HICACHE_MAX_SLAB_GB),
reusing the existing SharedHostTensorGroupAllocator + per-slab transfer splitting
(_host_transfer_segments). Each slab is one whole registration and no transfer
crosses a boundary; small configs (hicache_size<=400) stay single-slab unchanged.

- memory_pool_host.py: add cp_hicache_max_single_register_bytes() + the fail-loud
  _check_single_cuda_host_register_size guard; revert the (transfer-unsafe)
  registration chunking back to one cudaHostRegister per buffer/slab.
- hiradix_cache.py: _cp_shared_l2_slab_pages_by_payload auto-caps each payload's
  slab <= the ceiling so large caches auto-split.
- cp_l3_slab_accessor.py: CpSharedL2SlabAccessor is now slab-count-aware
  (CpL3SlabSpan + per-slab dispatch via global_base_page; per-slab layer stride);
  _cp_l3_slab_spans rewires _maybe_init_cp_l3 off the single-slab assumption. L3
  disk slabs / slot pool / LMDB index / GC are content-addressed and unchanged.

Tests: multi-slab accessor incl. a non-circular torch.frombuffer-layout check; a
real allocate_group + _cp_l3_slab_spans roundtrip; slab-cap auto-split; L3 store
cross-slab spill/reload. Reviewed by 3 adversarial agents, no correctness bugs.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-23 15:33:10 +00:00
..

Unit Tests

Component-level tests that do not launch a server or load model weights. Tests can use CPU or GPU — the key criterion is no server process.

Quick Start

  1. Find the source file under python/sglang/srt/.
  2. Create the corresponding test here, mirroring the source tree:
    srt/mem_cache/radix_cache.py       →  unit/mem_cache/test_radix_cache.py
    srt/sampling/sampling_params.py    →  unit/sampling/test_sampling_params.py
    
  3. Register for CI at the top of the file (after imports, before test classes):
    from sglang.test.ci.ci_register import register_cpu_ci
    register_cpu_ci(est_time=5, suite="stage-a-test-cpu")
    # or: register_cuda_ci(est_time=10, suite="stage-b-test-1-gpu-small")
    
  4. Run locally:
    pytest test/registered/unit/ -v            # all unit tests
    pytest test/registered/unit/mem_cache/ -v  # one module
    
  5. Run with coverage:
    # summary
    pytest test/registered/unit/ --cov --cov-config=.coveragerc -v
    
    # PR incremental check (require ≥60% on changed lines)
    pytest test/registered/unit/ --cov --cov-config=.coveragerc --cov-report=xml
    diff-cover coverage.xml --compare-branch=origin/main --fail-under=60
    

Example

"""Unit tests for <module> — no server, no model loading."""

from sglang.test.ci.ci_register import register_cpu_ci

register_cpu_ci(est_time=5, suite="stage-a-test-cpu")

import unittest

from sglang.srt.<module> import TargetClass
from sglang.test.test_utils import CustomTestCase


class TestTargetClass(CustomTestCase):
    def test_basic_behavior(self):
        obj = TargetClass(...)
        self.assertEqual(obj.method(), expected)


if __name__ == "__main__":
    unittest.main()

Rules

  • No popen_launch_server() or Engine(...).
  • No model weight loading.
  • Use CustomTestCase (from sglang.test.test_utils, adds CI retry).
  • Use unittest.mock for dependencies that are expensive to construct.