Commit Graph

3 Commits

Author SHA1 Message Date
mukesh e9cc40f74d Rectangular SIP topology + 6-device allreduce sweep
mesh_2d, torus_2d, and mesh_2d_no_wrap accept optional w,h kwargs;
sqrt fall-back preserved for square layouts (back-compat tests
confirm 4-SIP and 9-SIP square configs still work). sfr_config
reads system.sips.w/h from spec and threads dims through to the
topology fn.

test_allreduce_multidevice CONFIGS switched from 4 SIPs (square)
to 6 SIPs: ring_1d_6sip, torus_2d_6sip_2x3, mesh_2d_no_wrap_6sip_2x3.
_write_temp_configs writes system.sips.w/h when supplied;
_sip_topo_dims reads them back. Latency sweep loop also moved to
6-SIP layouts. Linear-scale plot variants dropped -- only log-scale
*.png + summary.csv emitted. Plots in tests/allreduce_latency_plots
regenerated.

New tests/test_sip_topology_rectangular.py asserts neighbor
correctness for 2x3 layouts and back-compat for square fallback.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-27 15:13:14 -07:00
mukesh 19dfc86dc3 Allreduce latency sweep across topologies and data sizes
Adds test_allreduce_latency_sweep that runs the existing intercube
allreduce kernel under three SIP topologies (ring_1d, torus_2d,
mesh_2d_no_wrap, all at n_sips=4) across 11 data sizes from 256 B/SIP
up to 1 MB/SIP. For each point, captures max(pe_exec_ns) — the
critical-path kernel time — and emits CSV plus log-x and linear-x
plots, both per-topology and combined overview, with KB/MB-formatted
tick labels. Reuses run_allreduce + _write_temp_configs and adds a
slot_size auto-bump when n_elem*2 exceeds the default IPCQ slot.

Sweep skips n_elem=16 because the runtime's dim_map scalar-arg
remapping (context.py:761) collides any int-valued kernel scalar that
matches a global tensor dim with its local shard size.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-27 10:16:29 -07:00
mukesh 1d8b9401e5 Intercube allreduce: pe0 cube-mesh reduce + multi-SIP ring/torus/mesh
New intercube allreduce kernel replacing the old flat ring algorithms.
Reduces across the 4x4 cube mesh within each SIP (pe0-only, same-lane),
then inter-SIP exchange on root cube, then broadcast back. Supports
ring_1d, torus_2d, and mesh_2d_no_wrap SIP topologies driven by
topology.yaml. Integrated with dist.init_process_group / dist.all_reduce.

New files:
- src/kernbench/ccl/algorithms/intercube_allreduce.py (kernel)
- src/kernbench/ccl/sfr_config.py (configure_sfr_intercube_multisip)
- tests/test_allreduce_multidevice.py (config-driven, 3 topologies)
- tests/test_distributed_intercube_allreduce.py (full distributed path)
- tests/test_intercube_sfr_config.py (SFR wiring verification)

Modified:
- distributed.py: AhbmCCLBackend uses configure_sfr_intercube_multisip
- topologies.py: added torus_2d, mesh_2d_no_wrap
- install.py: global_E/W/N/S in _OPPOSITE_DIR
- topology.yaml: added system.sips.topology
- ccl.yaml: single intercube_allreduce algorithm
- benches/ccl_allreduce.py: row_wise cube-mesh tensor layout

Removed old flat-ring algorithms and their tests.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-04-16 17:33:42 -07:00