Fix all remaining test failures: single-cube allreduce + matplotlib dep

- intercube_allreduce: add single-cube fast path that skips intra-SIP
  mesh reduce and goes directly to inter-SIP exchange. Fixes IPCQ
  deadlock when TP launches kernel on one cube per SIP.
- distributed.py: derive effective cube dims from tensor shard placement
  instead of hardcoding topology mesh size.
- pyproject.toml: add matplotlib>=3.7 to dependencies.
- pe_dma.py (prior commit): add MMU translation in pipeline DMA path.

577 passed, 0 failed (was 529 passed, 10 failed).

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

tests/allreduce_latency_plots/summary.csv

@@ -1,37 +1,37 @@
-algorithm,sip_topology,n_sips,n_elem,bytes_per_pe,bytes_per_sip,latency_ns
-intercube_allreduce,mesh_2d_no_wrap,6,8,16,256,3508.4249999999993
-intercube_allreduce,mesh_2d_no_wrap,6,32,64,1024,3515.55
-intercube_allreduce,mesh_2d_no_wrap,6,64,128,2048,3525.0499999999975
-intercube_allreduce,mesh_2d_no_wrap,6,128,256,4096,3544.049999999992
-intercube_allreduce,mesh_2d_no_wrap,6,512,1024,16384,3667.049999999992
-intercube_allreduce,mesh_2d_no_wrap,6,1024,2048,32768,3837.049999999992
-intercube_allreduce,mesh_2d_no_wrap,6,2048,4096,65536,4177.049999999992
-intercube_allreduce,mesh_2d_no_wrap,6,4096,8192,131072,4857.049999999959
-intercube_allreduce,mesh_2d_no_wrap,6,8192,16384,262144,6217.049999999945
-intercube_allreduce,mesh_2d_no_wrap,6,16384,32768,524288,8937.049999999937
-intercube_allreduce,mesh_2d_no_wrap,6,32768,65536,1048576,14377.049999999872
-intercube_allreduce,mesh_2d_no_wrap,6,49152,98304,1572864,19817.049999999872
-intercube_allreduce,ring_1d,6,8,16,256,3073.1299999999937
-intercube_allreduce,ring_1d,6,32,64,1024,3079.8799999999947
-intercube_allreduce,ring_1d,6,64,128,2048,3088.879999999992
-intercube_allreduce,ring_1d,6,128,256,4096,3106.8799999999865
-intercube_allreduce,ring_1d,6,512,1024,16384,3225.8799999999865
-intercube_allreduce,ring_1d,6,1024,2048,32768,3391.8799999999865
-intercube_allreduce,ring_1d,6,2048,4096,65536,3723.8799999999865
-intercube_allreduce,ring_1d,6,4096,8192,131072,4387.879999999965
-intercube_allreduce,ring_1d,6,8192,16384,262144,5715.879999999957
-intercube_allreduce,ring_1d,6,16384,32768,524288,8371.879999999932
-intercube_allreduce,ring_1d,6,32768,65536,1048576,13683.879999999903
-intercube_allreduce,ring_1d,6,49152,98304,1572864,18995.879999999917
-intercube_allreduce,torus_2d,6,8,16,256,2190.4799999999923
-intercube_allreduce,torus_2d,6,32,64,1024,2196.479999999993
-intercube_allreduce,torus_2d,6,64,128,2048,2204.4799999999905
-intercube_allreduce,torus_2d,6,128,256,4096,2220.479999999985
-intercube_allreduce,torus_2d,6,512,1024,16384,2325.479999999985
-intercube_allreduce,torus_2d,6,1024,2048,32768,2471.479999999985
-intercube_allreduce,torus_2d,6,2048,4096,65536,2763.479999999985
-intercube_allreduce,torus_2d,6,4096,8192,131072,3347.4799999999777
-intercube_allreduce,torus_2d,6,8192,16384,262144,4515.4799999999705
-intercube_allreduce,torus_2d,6,16384,32768,524288,6851.479999999952
-intercube_allreduce,torus_2d,6,32768,65536,1048576,11523.479999999923
-intercube_allreduce,torus_2d,6,49152,98304,1572864,16195.479999999952
+algorithm,sip_topology,n_sips,n_elem,bytes_per_pe,bytes_per_sip,latency_ns
+intercube_allreduce,mesh_2d_no_wrap,6,8,16,256,3508.4249999999993
+intercube_allreduce,mesh_2d_no_wrap,6,32,64,1024,3515.55
+intercube_allreduce,mesh_2d_no_wrap,6,64,128,2048,3525.0499999999975
+intercube_allreduce,mesh_2d_no_wrap,6,128,256,4096,3544.049999999992
+intercube_allreduce,mesh_2d_no_wrap,6,512,1024,16384,3667.049999999992
+intercube_allreduce,mesh_2d_no_wrap,6,1024,2048,32768,3837.049999999992
+intercube_allreduce,mesh_2d_no_wrap,6,2048,4096,65536,4177.049999999992
+intercube_allreduce,mesh_2d_no_wrap,6,4096,8192,131072,4857.049999999959
+intercube_allreduce,mesh_2d_no_wrap,6,8192,16384,262144,6217.049999999945
+intercube_allreduce,mesh_2d_no_wrap,6,16384,32768,524288,8937.049999999937
+intercube_allreduce,mesh_2d_no_wrap,6,32768,65536,1048576,14377.049999999872
+intercube_allreduce,mesh_2d_no_wrap,6,49152,98304,1572864,19817.049999999872
+intercube_allreduce,ring_1d,6,8,16,256,3073.1299999999937
+intercube_allreduce,ring_1d,6,32,64,1024,3079.8799999999947
+intercube_allreduce,ring_1d,6,64,128,2048,3088.879999999992
+intercube_allreduce,ring_1d,6,128,256,4096,3106.8799999999865
+intercube_allreduce,ring_1d,6,512,1024,16384,3225.8799999999865
+intercube_allreduce,ring_1d,6,1024,2048,32768,3391.8799999999865
+intercube_allreduce,ring_1d,6,2048,4096,65536,3723.8799999999865
+intercube_allreduce,ring_1d,6,4096,8192,131072,4387.879999999965
+intercube_allreduce,ring_1d,6,8192,16384,262144,5715.879999999957
+intercube_allreduce,ring_1d,6,16384,32768,524288,8371.879999999932
+intercube_allreduce,ring_1d,6,32768,65536,1048576,13683.879999999903
+intercube_allreduce,ring_1d,6,49152,98304,1572864,18995.879999999917
+intercube_allreduce,torus_2d,6,8,16,256,2190.4799999999923
+intercube_allreduce,torus_2d,6,32,64,1024,2196.479999999993
+intercube_allreduce,torus_2d,6,64,128,2048,2204.4799999999905
+intercube_allreduce,torus_2d,6,128,256,4096,2220.479999999985
+intercube_allreduce,torus_2d,6,512,1024,16384,2325.479999999985
+intercube_allreduce,torus_2d,6,1024,2048,32768,2471.479999999985
+intercube_allreduce,torus_2d,6,2048,4096,65536,2763.479999999985
+intercube_allreduce,torus_2d,6,4096,8192,131072,3347.4799999999777
+intercube_allreduce,torus_2d,6,8192,16384,262144,4515.4799999999705
+intercube_allreduce,torus_2d,6,16384,32768,524288,6851.479999999952
+intercube_allreduce,torus_2d,6,32768,65536,1048576,11523.479999999923
+intercube_allreduce,torus_2d,6,49152,98304,1572864,16195.479999999952