)]}'
{
  "commit": "8418badedc4a737e018322c1b751ea33af2b0cf7",
  "tree": "75d5e598abcaf9fe66936eacbbbc4f68351b8a2a",
  "parents": [
    "b2bc71346627dad9956c0e48ed5d216c5e4ee631"
  ],
  "author": {
    "name": "Frank Barchard",
    "email": "fbarchard@google.com",
    "time": "Tue May 13 09:55:57 2025"
  },
  "committer": {
    "name": "XNNPACK Team",
    "email": "xnnpack-github-robot@google.com",
    "time": "Tue May 13 11:03:29 2025"
  },
  "message": "F32-VSQRT for Hexagon\n\n- Implement xnn_rsqrt_f32 for simd/f32-hvx.h use Carmack approximation\n- Add portable simd.c.in template for hvx\n\n34.65x faster than scalar_approx_rsqrt on Samsung S23\nxnn_f32_vrsqrt_ukernel__hvx_u32/N:32640/real_time                     24841 ns\nxnn_f32_vrsqrt_ukernel__hvx_u64/N:32640/real_time                     13128 ns\nxnn_f32_vrsqrt_ukernel__hvx_u128/N:32640/real_time                     8642 ns\nxnn_f32_vrsqrt_ukernel__scalar_rsqrt_u1/N:32640/real_time           2293708 ns\nxnn_f32_vrsqrt_ukernel__scalar_rsqrt_u2/N:32640/real_time           2310264 ns\nxnn_f32_vrsqrt_ukernel__scalar_rsqrt_u4/N:32640/real_time           2200541 ns\nxnn_f32_vrsqrt_ukernel__scalar_approx_rsqrt_u1/N:32640/real_time     790721 ns\nxnn_f32_vrsqrt_ukernel__scalar_approx_rsqrt_u2/N:32640/real_time     444373 ns\nxnn_f32_vrsqrt_ukernel__scalar_approx_rsqrt_u4/N:32640/real_time     299529 ns\nxnn_f32_vsqrt_ukernel__scalar_sqrt_u1/N:32640/real_time             1123451 ns\nxnn_f32_vsqrt_ukernel__scalar_sqrt_u2/N:32640/real_time             1217916 ns\nxnn_f32_vsqrt_ukernel__scalar_sqrt_u4/N:32640/real_time             1206876 ns\n\nPiperOrigin-RevId: 758132404\n",
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