remove saxpy ci

[superlopuh]

I'm not sure we want this any more, the script it calls is becoming more and more different to the ones we'll actually be calling to generate the plots in the paper.

[github-actions]

kernels	baseline	linalg	scf_xdsl	snitch_stream	snrt	min_llvm_mlir
conv2d_d1_s1_3x3 1x1x8x8xf64	1569	1491		1504	1488	1491
ddot 128xf64	961	957	2245	205	569	957
dense 8x8xf64	3240	3257		2729	2737	3240
dsum 8x16xf32	1224	809	5480	177	198	809
fill 16x16xf64	349	349	2647	291	289	349
matmul 4x4x4xf64				207
matmul 8x8x8xf64	2517	2829		648	2325	2517
pooling_nchw_max_d1_s2_3x3 1x1x16x16xf64	1447	1194		1114	1099	1194
pooling_nchw_sum_d1_s2_3x3 1x1x16x16xf64	1940	1940		1996	1981	1940
relu 16x16xf64	1096	1086	7556	335	324	1086

[github-actions]

kernels	baseline	linalg	scf_xdsl	snitch_stream	snrt
conv2d_d1_s1_3x3 1x1x8x8xf64	0.23	0.22		0.22	0.22
ddot 128xf64	0.13	0.13	0.06	0.66	0.23
dense 8x8xf64	0.20	0.20		0.24	0.23
dsum 8x16xf32	0.11	0.16	0.02	0.73	0.65
fill 16x16xf64	0.00	0.00	0.00	0.89	0.89
matmul 4x4x4xf64				0.31
matmul 8x8x8xf64	0.20	0.18		0.79	0.28
pooling_nchw_max_d1_s2_3x3 1x1x16x16xf64	0.31	0.37		0.40	0.40
pooling_nchw_sum_d1_s2_3x3 1x1x16x16xf64	0.23	0.23		0.22	0.22
relu 16x16xf64	0.24	0.24	0.03	0.77	0.80

[github-actions]

kernels	baseline	linalg	scf_xdsl	snitch_stream	snrt	min_llvm_mlir
conv2d_d1_s1_3x3 1x1x8x8xf64	1569	1491		1504	1488	1491
ddot 128xf64	961	957	2245	205	569	957
dense 8x8xf64	3240	3257		2729	2737	3240
dsum 8x16xf32	1224	809	5480	177	198	809
fill 16x16xf64	349	349	2647	291	289	349
matmul 4x4x4xf64				207
matmul 8x8x8xf64	2517	2829		648	2325	2517
pooling_nchw_max_d1_s2_3x3 1x1x16x16xf64	1447	1194		1114	1099	1194
pooling_nchw_sum_d1_s2_3x3 1x1x16x16xf64	1940	1940		1996	1981	1940
relu 16x16xf64	1096	1086	7556	335	324	1086

[github-actions]

kernels	baseline	linalg	scf_xdsl	snitch_stream	snrt
conv2d_d1_s1_3x3 1x1x8x8xf64	0.23	0.22		0.22	0.22
ddot 128xf64	0.13	0.13	0.06	0.66	0.23
dense 8x8xf64	0.20	0.20		0.24	0.23
dsum 8x16xf32	0.11	0.16	0.02	0.73	0.65
fill 16x16xf64	0.00	0.00	0.00	0.89	0.89
matmul 4x4x4xf64				0.31
matmul 8x8x8xf64	0.20	0.18		0.79	0.28
pooling_nchw_max_d1_s2_3x3 1x1x16x16xf64	0.31	0.37		0.40	0.40
pooling_nchw_sum_d1_s2_3x3 1x1x16x16xf64	0.23	0.23		0.22	0.22
relu 16x16xf64	0.24	0.24	0.03	0.77	0.80