There are two implementations here:
- a generic scalable one processing two columns at a time,
- a specialised processing one (fixed-size) row at a time.
Unsurprisingly, the generic one works out better with smaller widths.
With larger widths, the gains from filling vectors are outweighed by
the extra cost of strided loads and stores. In other words, memory
accesses become the bottleneck.
T-Head C908:
h264_weight2_8_c: 54.5
h264_weight2_8_rvv_i32: 13.7
h264_weight4_8_c: 101.7
h264_weight4_8_rvv_i32: 27.5
h264_weight8_8_c: 197.0
h264_weight8_8_rvv_i32: 75.5
h264_weight16_8_c: 385.0
h264_weight16_8_rvv_i32: 74.2
SpacemiT X60:
h264_weight2_8_c: 48.5
h264_weight2_8_rvv_i32: 8.2
h264_weight4_8_c: 90.7
h264_weight4_8_rvv_i32: 16.5
h264_weight8_8_c: 175.0
h264_weight8_8_rvv_i32: 37.7
h264_weight16_8_c: 342.2
h264_weight16_8_rvv_i32: 66.0
Rémi Denis-Courmont
3606e592ea