bc23a81884
Shared CP KV materialization remained on the critical path for cached NSA/MLA prefill batches. This change introduces a one-layer-ahead prefetcher that materializes the cached prefix for the next layer on a separate CUDA stream and consumes it when that layer reaches attention. The prefetch path keeps the existing dense page-table semantics, defers waiting until the prefetched buffer is actually consumed, and uses the TAI optimized materialize/remap helpers when enabled before falling back to the torch implementation. The implementation is intentionally gated by environment variables and keeps layer-2-only probe logging for functional confirmation without making normal profiling noisy. Constraint: Prefill CP shared KV must preserve existing page-table and dense KV semantics for NSA paged topk attention Constraint: The production performance path requires SGLANG_CP_SHARED_KV_USE_TAI_MATERIALIZE=1 and logging disabled Rejected: Wait immediately after the producer layer attention | this truncated the overlap window and hid less work Rejected: Torch-only prefetch materialize | it bypassed the optimized TAI materialize/remap path and could erase the expected win Confidence: medium Scope-risk: moderate Directive: Do not evaluate Phase8 throughput with SGLANG_CP_SHARED_KV_LOG_MLA_PREFETCH=1; use it only to confirm create/start/consume_hit behavior Tested: Local AST parse for modified Python files Tested: Local git diff --check Tested: Remote g0034 container AST parse for modified files under /sgl-workspace/sglang-tai Tested: Remote g0034 container pytest target covering Phase8 log env, TAI range materialize, optimized slot inverse/remap, and existing token TAI path Not-tested: Full prefill/decode/router throughput after the TAI prefetch-path fix
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.