matmul-analysis/BMM/BMM_Theory/examples/result_evaluate.csv

1	case_id	batch_a	batch_b	m	n	k	dtype_a	dtype_b	dtype_c	trans_a	trans_b	has_bias	out_nd	deterministic_level	plan_case_id	plan_branch	plan_npu	plan_op	plan_used_core_num	plan_split_b	plan_m_cnt	plan_n_cnt	plan_grid_k	plan_core_map	plan_b_core	plan_merge_b0	plan_single_core_m	plan_single_core_n	plan_single_core_k	plan_k_l1	plan_b_l1	plan_l1_form	plan_base_m	plan_base_n	plan_base_k	plan_l2_policy_in	plan_l2_policy_out	plan_swizzle_w	plan_workspace_bytes	plan_tail_strategy	plan_tail_m_cnt	plan_tail_n_cnt	plan_tail_k_cnt	plan_tail_m_main	plan_tail_n_main	plan_tail_block_cnt	plan_tail_wave_num	plan_fixpipe_unitflag	plan_out_dtype_bytes	plan_note	gm_read_bytes	l2_read_bytes	t_mte2_gm	t_mte2_l2	t_mte2	dma_cmd_count	t_dma_cmd	cube_flops	t_mmad	fixpipe_bytes	t_fixpipe	t_reduce	t_steady	t_drain	t_total	bottleneck	feasible	violations	bound_type	advice
2	to_matmul_demo	1	1	2048	2048	2048	bf16	bf16	bf16	False	False	False	True	0	to_matmul_demo	转Matmul	Ascend950PR	batch_mat_mul_v3	32	1	0	0	1	折叠为 Matmul [2048,2048]x[2048,2048], 复用 Matmul 切分体系	0	1	0	0	2048	0	1		0	0	0			0	0	转Matmul后由 Matmul 体系决定	1	1	1	0	0	0	0	True	2	BatchB=1免费折叠: 左矩阵 [1,2048,2048] 视图折叠为 [2048,2048], 零重排零 split	16777216	0.0	1.048576e-05	0.0	1.048576e-05	0.0	0.0	17179869184.0	3.534952506995885e-05	8388608	5.24288e-06	0.0	3.534952506995885e-05	0.0	3.534952506995885e-05	MMAD	True		计算Bound	瓶颈在 Cube 计算: 已接近理论算力上限, 检查是否有冗余计算 (MergeBatch 交叉项) 可消除
3	special_k0_demo	128	128	256	256	0	bf16	bf16	bf16	False	False	False	True	0	special_k0_demo	特殊分支	Ascend950PR	batch_mat_mul_v3	64	1	1	1	1	AIV 核间按行均分 (无 Cube tile 概念)	0	1	0	0	0	0	1	UB驻留(AIV)	0	0	0	allocate	direct_gm	0	0	不涉及(AIV逐元素)	1	1	1	0	0	0	0	False	2	K=0纯写值: 无任何计算, C=bias 或 0, 纯 AIV 写值; 按行均分到 AIV 核	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	0.0	16777216	1.048576e-05	0.0	1.048576e-05	0.0	1.048576e-05	FIXPIPE	True		写出Bound	瓶颈在 Fixpipe 写出: 检查输出 dtype (fp16/fp8 可减半写出量), 或评估输出驻留 L2 异步回写策略
4	special_k1_demo	128	128	256	256	1	bf16	bf16	bf16	False	False	False	True	0	special_k1_demo	特殊分支	Ascend950PR	batch_mat_mul_v3	64	1	1	1	1	AIV 核间按行均分 (无 Cube tile 概念)	0	1	0	0	1	0	1	UB驻留(AIV) UB乒乓	0	0	0	allocate	direct_gm	0	0	不涉及(AIV逐元素)	1	1	1	0	0	0	0	False	2	K=1逐元素乘: 退化为 C=A⊙B 无累加深度, Cube 16x16x16 粒度浪费 15/16; 走 AIV 通路 GM->UB->Mul->GM, UB乒乓 (B>=2*AIV 双batch乒乓流水)	131072	0.0	8.192e-08	0.0	8.192e-08	0.0	0.0	8388608.0	6.206060606060606e-07	16777216	1.048576e-05	0.0	1.048576e-05	0.0	1.048576e-05	FIXPIPE	True		写出Bound	瓶颈在 Fixpipe 写出: 检查输出 dtype (fp16/fp8 可减半写出量), 或评估输出驻留 L2 异步回写策略
5	merge_demo_k_trunc	2048	2048	32	32	256	bf16	bf16	bf16	False	False	False	True	0	merge_demo_k_trunc	MergeBatch	Ascend950PR	batch_mat_mul_v3	32	32	1	1	1	切B均分(核间零重复读零依赖)	64	4	128	128	256	256	8	合并驻留	128	128	128	allocate(GM->L1随路驻留L2)	direct_gm	0	0	不涉及(核内不切M/N)	1	1	1	0	0	0	0	True	2	b0=4 (L0C上限5.7/算存比上限19.0/b_core=64); K截断; 合并后单次DMA搬入 A'[128,256]+B'[256,128]	2097152	0.0	4.194304e-05	0.0	4.2743039999999997e-05	16.0	8.000000000000001e-07	134217728.0	8.837381267489712e-06	131072	2.62144e-06	0.0	4.2743039999999997e-05	3.0192408230452674e-07	4.3044964082304525e-05	MTE2_GM	True		访存Bound(GM)	瓶颈在 GM 搬入: 可考虑增大 tile 提升 dValue/单核搬移量, 或利用 L2 驻留吸收重复读 (MergeBatch/ASW swizzle 方向)
6	merge_iter_arbitrate	128	128	64	64	512	bf16	bf16	bf16	False	False	False	True	0	merge_iter_arbitrate	IterBatch	Ascend950PR	batch_mat_mul_v3	32	32	1	1	1	切B轮转分配(核间零重复读零依赖)	4	1	64	64	512	512	2	b_双batch乒乓	64	64	256	allocate(GM->L1随路驻留L2)	direct_gm(输出仅写一次,直写GM不占L2)	0	0	不涉及(核内不切M/N)	1	1	1	0	0	0	0	True	2	双batch乒乓: 2*(MK+KN)*dtype=256KB <= L1	524288	0.0	1.048576e-05	0.0	1.0685759999999999e-05	4	2.0000000000000002e-07	16777216.0	1.104672658436214e-06	32768	6.5536e-07	0.0	1.0685759999999999e-05	4.400081646090535e-07	1.1125768164609053e-05	MTE2_GM	True		访存Bound(GM)	瓶颈在 GM 搬入: 可考虑增大 tile 提升 dValue/单核搬移量, 或利用 L2 驻留吸收重复读 (MergeBatch/ASW swizzle 方向)
7	iter_demo_form_b	128	128	64	64	256	bf16	bf16	bf16	False	False	False	True	0	iter_demo_form_b	IterBatch	Ascend950PR	batch_mat_mul_v3	32	32	1	1	1	切B轮转分配(核间零重复读零依赖)	4	1	64	64	256	256	2	b_双batch乒乓	64	64	256	allocate(GM->L1随路驻留L2)	direct_gm(输出仅写一次,直写GM不占L2)	0	0	不涉及(核内不切M/N)	1	1	1	0	0	0	0	True	2	双batch乒乓: 2*(MK+KN)*dtype=128KB <= L1	262144	0.0	5.24288e-06	0.0	5.4428799999999995e-06	4	2.0000000000000002e-07	8388608.0	5.52336329218107e-07	32768	6.5536e-07	0.0	5.4428799999999995e-06	3.0192408230452674e-07	5.744804082304526e-06	MTE2_GM	True		访存Bound(GM)	瓶颈在 GM 搬入: 可考虑增大 tile 提升 dValue/单核搬移量, 或利用 L2 驻留吸收重复读 (MergeBatch/ASW swizzle 方向)
8	iter_demo_form_d	64	64	64	64	8192	bf16	bf16	bf16	False	False	False	True	0	iter_demo_form_d	IterBatch	Ascend950PR	batch_mat_mul_v3	32	32	1	1	1	切B轮转分配(核间零重复读零依赖)	2	1	64	64	8192	1024	1	d_两侧都切K	64	64	256	allocate(GM->L1随路驻留L2)	direct_gm(输出仅写一次,直写GM不占L2)	0	0	不涉及(核内不切M/N)	1	1	1	0	0	0	0	True	2	两侧都切K: k_L1=1024, K段成对流水, batch边界天然无缝; dValueA=2048B/dValueB=128B	4194304	0.0	8.388608e-05	0.0	8.468608e-05	16	8.000000000000001e-07	134217728.0	8.837381267489712e-06	16384	3.2768e-07	0.0	8.468608e-05	7.16176329218107e-07	8.540225632921811e-05	MTE2_GM	True		访存Bound(GM)	瓶颈在 GM 搬入: 可考虑增大 tile 提升 dValue/单核搬移量, 或利用 L2 驻留吸收重复读 (MergeBatch/ASW swizzle 方向)
9	streamk_demo	4	4	128	128	10240	bf16	bf16	bf16	False	False	False	True	0	streamk_demo	StreamK	Ascend950PR	batch_mat_mul_v3	32	1	1	1	32	B/M/N切出4块, 每块32核切K归约 (归约组内核c负责K段[c*K/32,(c+1)*K/32))	1	1	128	128	320	256	1	K段标准分块流水	128	128	64	allocate(部分和驻留L2)	resident(部分和4B驻留L2, 防精度丢失不随C的fp16/fp8转换)	0	8388608	grid_K=32路切K+归约	1	1	32	0	0	0	0	True	4	P=1.00, grid_K=32, 部分和驻留L2按4B写出, AIV归约后按C dtype=2B写最终	327680.0	0.0	6.5536e-06	0.0	6.5536e-06	0.0	0.0	41943040.0	2.761681646090535e-06	0.0	0.0	3.4067453613053613e-06	6.5536e-06	3.4067453613053613e-06	9.960345361305361e-06	MTE2_GM	True		访存Bound(GM)	瓶颈在 GM 搬入: 可考虑增大 tile 提升 dValue/单核搬移量, 或利用 L2 驻留吸收重复读 (MergeBatch/ASW swizzle 方向)
10	asw_demo_full	2	2	8192	8192	1024	bf16	bf16	bf16	False	False	False	True	0	asw_demo_full	ASW_Basic	Ascend950PR	batch_mat_mul_v3	32	1	47	47	1	B->M->N线性映射+ASW滑窗蛇形(W=4)	0	1	176	176	1024	256	1	双缓冲驻留当前tile输入	176	176	80	allocate(输入驻留L2吸收重复读)	direct_gm(输出直写GM不占L2)	4	0	方案B	52	52	1	52	52	2	139	True	2	L2场景B_输入驻留输出直写GM, r_in=1.00; 尾轮: 周长型主导, rho=0.06<rho_dv=0.53, A1b被dValue卡死, 方案B反超	67108864.0	0.0	4.194304e-05	0.0	4.194304e-05	0.0	0.0	274877906944.0	0.0005655924011193416	268435456	0.00016777216	0.0	0.0005655924011193416	0.0	0.0005655924011193416	MMAD	True		计算Bound	瓶颈在 Cube 计算: 已接近理论算力上限, 检查是否有冗余计算 (MergeBatch 交叉项) 可消除
11	asw_demo_reduce_core	16	16	256	256	128	bf16	bf16	bf16	False	False	False	True	0	asw_demo_reduce_core	ASW_Basic_降核	Ascend950PR	batch_mat_mul_v3	16	1	1	1	1	降核: 只用16核, 每核一个L0C满载输出块, 其余核闲置	0	1	256	256	128	128	1	标准核内流水	256	256	64	allocate	direct_gm	0	0	不涉及(每核一块无尾轮)	1	1	1	0	0	0	0	True	2	P=16.00<C, 降核是理性选择 (强切则 tile 跌破搬移效率下限反而更慢)	2097152.0	0.0	2.62144e-06	0.0	2.62144e-06	0.0	0.0	268435456.0	1.104672658436214e-06	2097152	2.62144e-06	0.0	2.62144e-06	0.0	2.62144e-06	MTE2_GM	True		访存Bound(GM)	瓶颈在 GM 搬入: 可考虑增大 tile 提升 dValue/单核搬移量, 或利用 L2 驻留吸收重复读 (MergeBatch/ASW swizzle 方向)