Fix cross-SIP PE_TCM access by scoping deploy to target_device SIP
RuntimeContext._ensure_allocators() now limits SIP range to target_device (single SIP or all). Prevents cross-SIP tensor deployment that caused PE_TCM routing errors. Also accept 'sip0' format (without colon) in DeviceSelector. 331 passed, 8 skipped Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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@@ -18,5 +18,5 @@ def test_cli_main_arg_parsing(monkeypatch):
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def test_cli_main():
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"""CLI bench run on single SIP device."""
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import pytest
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pytest.skip("Cross-SIP PE_TCM access not supported with router mesh topology")
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rc = cli_main.main(["run", "--topology", "topology.yaml", "--bench", "qkv_gemm", "--device", "sip:0"])
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assert rc == 0
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@@ -861,7 +861,6 @@ def test_mcpu_kernel_launch_composite():
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# ── 19. Stage 5: QKV GEMM benchmark completion ────────────────────
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@pytest.mark.skip(reason="Cross-SIP PE_TCM access not supported with router mesh topology")
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def test_qkv_gemm_bench_completes():
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"""The qkv_gemm benchmark runs to completion without error."""
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clear_registry()
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@@ -956,7 +955,6 @@ def test_mcpu_multi_pe_kernel_launch():
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# ── 21. Stage 5: QKV GEMM multi-PE benchmark completion ──────────
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@pytest.mark.skip(reason="Cross-SIP PE_TCM access not supported with router mesh topology")
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def test_qkv_gemm_bench_multi_pe_completes():
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"""The qkv_gemm_multi_pe benchmark runs to completion without error."""
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clear_registry()
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@@ -131,7 +131,6 @@ def test_2d_va_translates_to_local_hbm():
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# ── VO3. 2D: End-to-end bench completes ──────────────────────────────
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@pytest.mark.skip(reason="Cross-SIP PE_TCM access not supported with router mesh topology")
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def test_2d_bench_completes():
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"""2D: full TP bench with standard Triton kernel pattern."""
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graph = load_topology(TOPOLOGY_PATH)
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@@ -199,7 +198,6 @@ def test_1d_va_translates_to_local_hbm():
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# ── VO6. 1D: End-to-end ──────────────────────────────────────────────
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@pytest.mark.skip(reason="Cross-SIP PE_TCM access not supported with router mesh topology")
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def test_1d_e2e_completes():
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"""1D: full engine run with column_wise TP sharding."""
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graph = load_topology(TOPOLOGY_PATH)
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