ORBIT-2: EDM weak-scaling sweep (HSDP) + validated 1-8 node results - #40
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run_scaling_study.sh now honors ORBIT2_BATCH_SIZE/MAX_EPOCH/MAX_BATCHES overrides and sets HSDP parallelism per node count (fsdp=8 intra-node over XGMI, simple_ddp=N inter-node over IB/ANP) instead of the render default fsdp=N/simple_ddp=8, keeping per-rank work fixed for true weak scaling. Adds the Bayes-CAST EDM invocation and passes ORBIT2_ROOT/ERA5_SPATIAL_RES/ FUSED_ATTN through to sbatch. Documents the MI355X EDM weak-scaling result in the train recipe: clean scaling through 2 nodes (eff ~1.01), with 4/8-node efficiency flagged as a data-cap measurement artifact (steps/epoch collapse), motivating more staged ERA5. Captures the weak-vs-strong + HSDP lesson and the >1 efficiency pitfall in the earth-science skill. Co-authored-by: Cursor <cursoragent@cursor.com>
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Summary
Enables and documents a weak-scaling sweep of the Bayes-CAST EDM model for ORBIT-2 across 1/2/4/8 MI355X nodes, keeping each GPU compute-saturated at every node count.
run_scaling_study.sh— now honorsORBIT2_BATCH_SIZE/ORBIT2_MAX_EPOCH/ORBIT2_MAX_BATCHESoverrides (previously hardcoded), and sets HSDP parallelism per node count:fsdp=8within a node (XGMI) +simple_ddp=Nacross nodes (IB/ANP), instead of the render defaultfsdp=N/simple_ddp=8which would shard weights across the slow inter-node fabric. This keeps per-rank work fixed for true weak scaling. Adds the EDM invocation and passesORBIT2_ROOT/ORBIT2_ERA5_SPATIAL_RES/ORBIT2_FUSED_ATTNthrough to sbatch.recipes/train/README.md— adds the validated MI355X EDM weak-scaling table (bf16, per-rank batch 1024, ERA5 1.0°). Clean scaling is demonstrated through 2 nodes (efficiency ~1.01, flat step time = well-overlapped RCCL/IB comm); the 4/8-node efficiencies (>1.0) are explicitly flagged as a data-cap measurement artifact (steps/epoch collapse, sothroughput = global_batch/step_timeinflates), which motivates staging more ERA5..cursor/skills/ai4science-earth-science/SKILL.md— captures the weak-vs-strong + HSDP layout lesson and the ">1 efficiency" pitfall so future sessions checksteady_batch_countbefore quoting multi-node throughput.Notes
$AI4S_SHARED_DIR/env vars and placeholder partition/account; absolute cluster paths, account, and partition names were scrubbed from the recipe. Run artifacts (scaling_study.*) stay on shared storage, not in the repo.t_1node/t_Nnode, a comm-overlap/RCCL-bandwidth metric.Test plan