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# RL rollout pool, level4_huge members (staged into level_sparse/level4_huge/ by
# stage_rl_pool.py). Only matrices whose SpGEMM baseline the harness can run
# live on one GPU (cuSPARSE, 143 GB H200, C = A*A / A*A^T) -- see
# spgemm_excluded.txt for the ten level4 matrices that were dropped and why.
# Sources: test_set/level4_huge (4) and rl_pool/level4_huge regenerated by
# build_rl_pool.py from level4_regen_list.txt (8).
Bourchtein_atmosmodd
DIMACS10_delaunay_n24
Freescale_circuit5M_dc
Freescale_Freescale1
Freescale_memchip
Hamrle_Hamrle3
Janna_CoupCons3D
Schenk_AFE_af_shell10
Schmid_thermal2
SNAP_roadNet-CA
SNAP_roadNet-TX
Zaoui_kkt_power
# Matrices dropped from the SpGEMM RL rollout pool (build_dataset.py --exclude-from).
# Criterion: the harness must produce a cuSPARSE baseline live on one GPU
# (benchmark_spgemm, 143 GB H200), and a cuSPARSE-backed reference kernel that
# follows the kernel contract must run. Where that fails, every rollout scores
# -1/-0.5 regardless of the policy, i.e. zero learning signal per GRPO group.
# Checked 2026-09-12 with a cuSPARSE reference kernel (C = A*A, or A*A^T for
# rectangular A via Csr2cscEx2). Error 11 = CUSPARSE_STATUS_INSUFFICIENT_RESOURCES.
#
# --- level4_huge: harness baseline itself fails (no external HSMU dump) ---
DGL_reddit # cusparse_spgemm.cu:91 err 11 (A*A does not fit)
OGB_ogbn-proteins # cusparse_spgemm.cu:91 err 11
SNAP_wiki-Talk # cusparse_spgemm.cu:111 err 11 (power-law, A*A explodes)
SNAP_wiki-talk-temporal # cusparse_spgemm.cu:111 err 11
# --- level4_huge: baseline only via a precomputed dump in /mnt/data2/Dr.Sparse/spgemm_ref
# (SPGEMM_EXT_REF_DIR, not on the remote); live cuSPARSE runs out of memory,
# and the GPT-5.6 teacher never produced a >=1.05x kernel on any of them ---
Belcastro_human_gene1 # C nnz 224M; ref kernel err 11
Belcastro_mouse_gene # C nnz 483M; ref kernel err 11
DIMACS10_asia_osm # 12M rows; ref kernel err 11
Gupta_gupta3 # ref kernel err 11
LAW_in-2004 # ref kernel err 11
QY_case39 # ref kernel err 11
# --- level3_large: harness baseline itself fails ---
LAW_cnr-2000 # cusparse_spgemm.cu:111 err 11 (web graph, A*A explodes)

Dr.Sparse RL rollout pool, level4_huge members

The SpGEMM online-RL rollout pool is 130 SuiteSparse matrices: the 118 level1-3 matrices in the Dr.Sparse git repo (level_sparse/level{1_small,2_medium,3_large}) plus the 12 level4 matrices in this dataset. It is disjoint from the 100-matrix OTF test set.

The 12 level4 (>= 1.1M rows) matrices, in Dr.Sparse, in the repo's raw .bin layout ([int32 rows, cols, nnz][int32 row_ptr][int32 col_ind][float32 values][float32 x], read by level_sparse/data_loader.h). The level1-3 members (118 matrices) ship in the git repo; the 100-matrix OTF test set is KinGeorge/Dr.Sparse-OTF-test-set.

Stage into a checkout with:

python level_sparse/stage_rl_pool.py --download   # -> level_sparse/level4_huge/

level4_list.txt is the member list; spgemm_excluded.txt records the ten level4 matrices that were dropped because cuSPARSE cannot produce an SpGEMM baseline for them on one GPU. Values are the real matrix values (float32); x is a fixed standard-normal vector baked in at build time.

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