include snitch_stream variants in regalloc csv

[superlopuh]

We can filter down the ones we don't want later, but it's worth including the f32 variants in the regalloc.

[github-actions]

kernels,baseline,linalg,linalg_xdsl,snitch_stream,snrt
conv2d_d1_s1_3x3 4x4xf64,667,,308,,
ddot 128xf64,956,965,,213,577
dense 8x8xf64,3206,3530,,2741,2723
fill 4x4xf64,50,,63,,
matmul 4x16x8xf64,2495,,708,,
matmul_transb 4x16x16xf32,3386,,,871,849
pooling_nchw_max_d1_s2_3x3 4x4xf64,442,,275,,
pooling_nchw_sum_d1_s2_3x3 4x4xf64,582,,271,,
relu 4x4xf64,142,,72,,
relu 4x8xf32,297,210,,67,85
saxpy 64xf32,634,634,,,140
sum 4x4xf64,129,,87,,
sum 4x8xf32,238,247,87,,72
sum 8x8xf16,821,,65,,

[github-actions]

kernels,baseline,linalg,linalg_xdsl,snitch_stream,snrt
conv2d_d1_s1_3x3 4x4xf64,0.22,,0.58,,
ddot 128xf64,0.13,0.13,,0.64,0.22
dense 8x8xf64,0.20,0.18,,0.26,0.26
fill 4x4xf64,0.02,,0.29,,
matmul 4x16x8xf64,0.21,,0.82,,
matmul_transb 4x16x16xf32,0.21,,,0.77,0.79
pooling_nchw_max_d1_s2_3x3 4x4xf64,0.33,,0.65,,
pooling_nchw_sum_d1_s2_3x3 4x4xf64,0.22,,0.66,,
relu 4x4xf64,0.13,,0.25,,
relu 4x8xf32,0.33,0.16,,0.28,0.22
saxpy 64xf32,0.10,0.10,,,0.46
sum 4x4xf64,0.13,,0.20,,
sum 4x8xf32,0.14,0.13,0.20,,0.24
sum 8x8xf16,0.31,,0.26,,

[github-actions]

kernels,baseline,linalg,linalg_xdsl,snitch_stream,snrt
conv2d_d1_s1_3x3 4x4xf64,667,,308,,
ddot 128xf64,956,965,,213,577
dense 8x8xf64,3206,3530,,2741,2723
fill 4x4xf64,50,,63,,
matmul 4x16x8xf64,2495,,708,,
matmul_transb 4x16x16xf32,3386,,,871,849
pooling_nchw_max_d1_s2_3x3 4x4xf64,442,,275,,
pooling_nchw_sum_d1_s2_3x3 4x4xf64,582,,271,,
relu 4x4xf64,142,,72,,
relu 4x8xf32,297,210,,67,85
saxpy 64xf32,634,634,,,140
sum 4x4xf64,129,,87,,
sum 4x8xf32,238,247,87,,72
sum 8x8xf16,821,,65,,

[github-actions]

kernels,baseline,linalg,linalg_xdsl,snitch_stream,snrt
conv2d_d1_s1_3x3 4x4xf64,0.22,,0.58,,
ddot 128xf64,0.13,0.13,,0.64,0.22
dense 8x8xf64,0.20,0.18,,0.26,0.26
fill 4x4xf64,0.02,,0.29,,
matmul 4x16x8xf64,0.21,,0.82,,
matmul_transb 4x16x16xf32,0.21,,,0.77,0.79
pooling_nchw_max_d1_s2_3x3 4x4xf64,0.33,,0.65,,
pooling_nchw_sum_d1_s2_3x3 4x4xf64,0.22,,0.66,,
relu 4x4xf64,0.13,,0.25,,
relu 4x8xf32,0.33,0.16,,0.28,0.22
saxpy 64xf32,0.10,0.10,,,0.46
sum 4x4xf64,0.13,,0.20,,
sum 4x8xf32,0.14,0.13,0.20,,0.24
sum 8x8xf16,0.31,,0.26,,