feat(hipsr): add pool-alloc greedy grouping

[zz002]

Summary

-hipsr-pool-alloc now groups each pool domain's allocs by lifetime: an alloc joins the first group whose members are all disjoint from it, otherwise it opens a new one. The pass still rewrites nothing; the emit-pool-report remark gained the group each alloc landed in.

Related issue or design

Upstream wcy123/onnx-hipdnn-ep#110 (greedy grouping utility), a step of wcy123/onnx-hipdnn-ep#19, which links the HIPSR Pool Allocation Pass design page. Follows #591 (#109, liveness).

Why

Group numbering ends up in the report, and #117 will turn it into pool offsets, so it has to be reproducible. Two things make it so: allocs are collected by walking the block rather than iterating the Value -> Lifetime map, whose order is pointer-hash dependent; and the sort by lifetime start is stable, because allocs feeding several outs of one DPS op share a start and an unstable sort would order them arbitrarily.

Touching endpoints count as overlapping. The op that first writes the later buffer is still reading the earlier one, so [1,3] and [3,5] cannot share space.

What

• greedyGrouping(Block &, const DenseMap<Value, Lifetime> &) returning groups as vectors of allocs, next to computeLiveness in the same anonymous namespace.
• emitPoolingReport takes the groups and reports lifetime [a,b] group N. Per-domain totals (alloc and group counts, reuse ratio) belong to #118.
• pool_alloc_report.mlir: existing ranges gained their group, plus the two boundary topologies.

Test plan

• Full check-hip-mlir-lit — 361 passed, 3 unsupported, 0 failed.
• Mutation check: flipping one expected group N fails the run, so the new assertions are not vacuous.
• pre-commit run --all-files clean.

Grouping is covered by chromatic number of the interval graph: coalesce_static (four disjoint allocs of differing sizes, one group), interleaved_allocs and hoisted_allocs (one alloc over two disjoint ones, two groups), split_three_groups (pairwise overlap, three groups).

Notes for reviewers

• coalesce_static and split_three_groups are lifted verbatim from the reference implementation in #572, minus its CHECK lines, which assert the pooled IR that does not exist yet. Keeping the fixtures identical means #117 adds assertions instead of rewriting tests. They live in pool_alloc_report.mlir for now because a remark is the only thing to assert before the rewrite is wired; #117 moves them to pool_alloc.mlir.
• Tests are lit rather than gtest: the inputs are a Block and its Values, which gtest would have to build by hand, and the RUN line's --implicit-check-not=hipsr.get_pool --implicit-check-not=memref.view doubles as proof the pass is still a no-op. Happy to add a unit test if reviewers prefer one.
• greedyGrouping runs unconditionally and its result is only read under emit-pool-report, matching how computeLiveness landed in #109. #117 consumes it for real.

Checklist

• The change is focused, or links a design/series explaining its scope.
• Relevant tests were added or updated and the results are documented.
• User-facing or design documentation was updated when needed.
• Substantial AI assistance is disclosed, and I reviewed and understand the result.

AI assistance: Cursor implemented greedyGrouping, ported the two fixtures, and ran the lit and pre-commit validation above; I reviewed the result and hand-checked every expected lifetime and group against the fixture IR.

[github-actions]

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[github-actions]

L2 Accuracy Results (EP vs CPU)

Model	Combined L2	Total Elems	Skipped NaN/Inf
conv_test_hybrid	4.8668E-07	64	0
GroupQueryAttention_seq256	25.2366	2621440	0
MatMulNBits_o_seq128	259.906	368640	0
QMoE_seq128	34.9552	368640	0

Threshold: 0.01 | Run: 3452 - Commit: 3691f44

[github-actions]

MorphiZen EP Performance Results

Model	QPS	Session (s)	1st Infer (ms)	CPU%	Mem (MB)
full_model_seq128	7.51	6.26	367	3	1243
GroupQueryAttention_seq128	4391.36	1.68884	11	6	310
matmul_down_seq128	526.74	2.38	74	3	351

EPContext Export Performance

Model	QPS	Session (s)	1st Infer (ms)	CPU%	Mem (MB)
full_model_seq128	7.52	46.67	361	3	15590

EPContext Import Performance

Model	QPS	Session (s)	1st Infer (ms)	CPU%	Mem (MB)
full_model_seq128	7.51	9.77	359	3	15760

OGA Benchmark Results

Model	Warmup	Reps	Prompt Len	Gen Tokens	TTFT (ms)	TPS	Peak Mem (GB)	GPU Mem (GB)
gpt-oss-20b-webgpu-int4-rtn-block-32	1	5	128	128	175.0	79.4	1.33	13.54
Llama-3.1-8B-awq-g128-int4-asym-fp16-onnx-dml	1	5	128	128	226.5	40.8	1.22	6.43

OGA Wheel Smoke (Python benchmark_e2e.py)

Model	TTFT (ms)	TPS
Llama-3.1-8B-awq-g128-int4-asym-fp16-onnx-dml	202	39.6

Run: 3452 - Commit: 3691f44

[wcy123]

LGTM