Files
sglang/test/registered
leaveletandClaude Opus 4.8 6114c3e3e5 HiCache host pool: check hugepages, not regular RAM, for the hugetlbfs-backed (CP shared-L2) pool
The host-pool size check used psutil.virtual_memory().available -- regular RAM -- unconditionally. But
hugepages are carved OUT of regular RAM, so reserving e.g. 1 TB of 2M hugepages drops psutil.available
by ~1 TB, and the check then spuriously fails ("Not enough host memory ... only have 897 GB free") even
though the slab is allocated from the hugepages, not regular RAM. It was inspecting the wrong pool.

Two fixes:
- memory_pool_host.py: gate the psutil check on the DEFAULT (regular-malloc) allocator. A custom
  host_tensor_allocator (the CP shared-L2 slab over hugetlbfs) owns its own capacity check, so skip the
  regular-RAM check for it.
- cp_shared_l2_pool.py: add cp_shared_l2_hugetlbfs_free_bytes() + check_cp_shared_l2_hugetlbfs_capacity()
  (statvfs the hugetlbfs mount: f_frsize = hugepage size, f_bavail = free hugepages) and call it in
  create_cp_shared_host_slab before ftruncate/mmap. Now insufficient hugepages fail LOUD with a clean,
  actionable message ("insufficient hugepages in /dev/hugepages: need X GB (N x 2M pages) but only Y GB
  free; reserve more or reduce --hicache-size") instead of a cryptic mmap ENOMEM. Per-slab + sequential,
  so each payload's slab sees the free remaining after the prior ones.

Unit-tested (capacity check: tiny fits, over-capacity fails loud). Pre-existing 2b L2-pooling code (not L3).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-23 10:17:33 +00:00
..
2026-03-21 17:10:35 +08:00

Registered Tests

Tests under this directory are auto-discovered by run_suite.py via CI registration decorators.

Where Should I Put My New Test?

No server / engine launch required

What you're testing Directory Requires
Component logic in isolation (cache, scheduler, config, parser, etc.) unit/<module>/ CPU or GPU
CUDA kernel correctness kernels/ GPU

Server / engine launch required (E2E)

What you're testing Directory Requires
Model inference correctness models/, 4-gpu-models/, 8-gpu-models/ GPU
Feature-specific (OpenAI API, LoRA, speculative, distributed, VLM, etc.) openai_server/, lora/, spec/, distributed/, ... GPU
Benchmarks (performance, accuracy, stress) benchmark/ GPU
Platform-specific amd/, ascend/ Vendor GPU

See unit/README.md for unit test conventions.