xref: /aosp_15_r20/external/XNNPACK/src/bf16-gemm/c8-neonbf16.c.in (revision 4bdc94577ba0e567308109d787f7fec7b531ce36)
1// Copyright 2022 Google LLC
2//
3// This source code is licensed under the BSD-style license found in the
4// LICENSE file in the root directory of this source tree.
5
6$assert NR % 4 == 0
7$assert BFOPT in ["BFDOT", "BFMLAL"]
8$ABC = "0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ"
9
10#include <assert.h>
11
12#include <arm_neon.h>
13
14#include <xnnpack/gemm.h>
15
16
17void xnn_bf16_gemm_minmax_ukernel_${MR}x${NR}c8__neonbf16_${BFOPT.lower()}(
18    size_t mr,
19    size_t nc,
20    size_t kc,
21    const void* restrict a,
22    size_t a_stride,
23    const void* restrict w_ptr,
24    void* restrict c,
25    size_t cm_stride,
26    size_t cn_stride,
27    const union xnn_bf16_minmax_params params[restrict XNN_MIN_ELEMENTS(1)])
28{
29  assert(mr != 0);
30  assert(mr <= ${MR});
31  assert(nc != 0);
32  assert(kc != 0);
33  assert(kc % sizeof(bfloat16_t) == 0);
34  assert(a != NULL);
35  assert(w_ptr != NULL);
36  assert(c != NULL);
37
38  const bfloat16_t* a0 = (const bfloat16_t*) a;
39  bfloat16_t* c0 = (bfloat16_t*) c;
40  $for M in range(1, MR):
41    const bfloat16_t* a${M} = (const bfloat16_t*) ((uintptr_t) a${M-1} + a_stride);
42    bfloat16_t* c${M} = (bfloat16_t*) ((uintptr_t) c${M-1} + cm_stride);
43    $if M % 2 == 0:
44      if XNN_UNPREDICTABLE(mr <= ${M}) {
45        a${M} = a${M-1};
46        c${M} = c${M-1};
47      }
48    $elif M + 1 == MR:
49      if XNN_UNPREDICTABLE(mr != ${M+1}) {
50        a${M} = a${M-1};
51        c${M} = c${M-1};
52      }
53    $else:
54      if XNN_UNPREDICTABLE(mr < ${M+1}) {
55        a${M} = a${M-1};
56        c${M} = c${M-1};
57      }
58
59  const bfloat16_t* w = (const bfloat16_t*) w_ptr;
60  do {
61    $for N in range(NR):
62      float32x4_t vacc0x${ABC[N]} = vcvt_f32_bf16(vld1_lane_bf16(w, vreinterpret_bf16_u16(vdup_n_u16(0)), 0)); w += 1;
63    $for M in range(1, MR):
64      $for N in range(NR):
65        float32x4_t vacc${M}x${ABC[N]} = vacc0x${ABC[N]};
66
67    size_t k = kc;
68    for (; k >= 8 * sizeof(bfloat16_t); k -= 8 * sizeof(bfloat16_t)) {
69      $for M in range(MR):
70        const bfloat16x8_t va${M} = vld1q_bf16(a${M}); a${M} += 8;
71
72      $for N in range(NR):
73        const bfloat16x8_t vb${ABC[N]} = vld1q_bf16(w); w += 8;
74
75      $if BFOPT == "BFDOT":
76        $for N in range(NR):
77          $for M in range(MR):
78            vacc${M}x${ABC[N]} = vbfdotq_f32(vacc${M}x${ABC[N]}, va${M}, vb${ABC[N]});
79      $elif BFOPT == "BFMLAL":
80        $for N in range(NR):
81          $for M in range(MR):
82            vacc${M}x${ABC[N]} = vbfmlalbq_f32(vacc${M}x${ABC[N]}, va${M}, vb${ABC[N]});
83
84        $for N in range(NR):
85          $for M in range(MR):
86            vacc${M}x${ABC[N]} = vbfmlaltq_f32(vacc${M}x${ABC[N]}, va${M}, vb${ABC[N]});
87    }
88    if XNN_UNLIKELY(k != 0) {
89      $for M in range(MR):
90        const bfloat16x8_t va${M} = vld1q_bf16(a${M}); a${M} = (const bfloat16_t*) ((uintptr_t) a${M} + k);
91
92      $for N in range(NR):
93        const bfloat16x8_t vb${ABC[N]} = vld1q_bf16(w); w += 8;
94
95      $for N in range(NR):
96        const uint16x8_t vm${ABC[N]} = vceqq_u16(vreinterpretq_u16_bf16(vb${ABC[N]}), vmovq_n_u16(0));
97
98      $for N in range(NR):
99        $for M in range(MR):
100          const bfloat16x8_t va${M}x${ABC[N]} = vreinterpretq_bf16_u16(vbicq_u16(vreinterpretq_u16_bf16(va${M}), vm${ABC[N]}));
101          $if BFOPT == "BFDOT":
102            vacc${M}x${ABC[N]} = vbfdotq_f32(vacc${M}x${ABC[N]}, va${M}x${ABC[N]}, vb${ABC[N]});
103          $elif BFOPT == "BFMLAL":
104            vacc${M}x${ABC[N]} = vbfmlalbq_f32(vacc${M}x${ABC[N]}, va${M}x${ABC[N]}, vb${ABC[N]});
105            vacc${M}x${ABC[N]} = vbfmlaltq_f32(vacc${M}x${ABC[N]}, va${M}x${ABC[N]}, vb${ABC[N]});
106    }
107
108#if XNN_ARCH_ARM64
109    $for N in range(0, NR, 2):
110      $for M in range(MR):
111        const float32x4_t vacc${M}x${ABC[N:N+2]} = vpaddq_f32(vacc${M}x${ABC[N]}, vacc${M}x${ABC[N+1]});
112
113    $for N in range(0, NR, 4):
114      $for M in range(MR):
115        float32x4_t vacc${M}x${ABC[N:N+4]} = vpaddq_f32(vacc${M}x${ABC[N:N+2]}, vacc${M}x${ABC[N+2:N+4]});
116#else
117    $for N in range(NR):
118      $for M in range(MR):
119        const float32x2_t vsum${M}x${ABC[N]} = vadd_f32(vget_low_f32(vacc${M}x${ABC[N]}), vget_high_f32(vacc${M}x${ABC[N]}));
120
121    $for N in range(0, NR, 4):
122      $for M in range(MR):
123        float32x4_t vacc${M}x${ABC[N:N+4]} = vcombine_f32(vpadd_f32(vsum${M}x${ABC[N]}, vsum${M}x${ABC[N+1]}), vpadd_f32(vsum${M}x${ABC[N+2]}, vsum${M}x${ABC[N+3]}));
124#endif
125
126    const float32x4_t vmax = vld1q_dup_f32(&params->scalar.max);
127    $for N in range(0, NR, 4):
128      $for M in range(MR):
129        vacc${M}x${ABC[N:N+4]} = vminq_f32(vacc${M}x${ABC[N:N+4]}, vmax);
130
131    const float32x4_t vmin = vld1q_dup_f32(&params->scalar.min);
132    $for N in range(0, NR, 4):
133      $for M in range(MR):
134        vacc${M}x${ABC[N:N+4]} = vmaxq_f32(vacc${M}x${ABC[N:N+4]}, vmin);
135
136    $for N in range(0, NR, 4):
137      $for M in range(MR):
138        bfloat16x4_t vout${M}x${ABC[N:N+4]} = vcvt_bf16_f32(vacc${M}x${ABC[N:N+4]});
139
140    if XNN_LIKELY(nc >= ${NR}) {
141      $for M in range(MR):
142        vst1_bf16(c${M}, vout${M}x${ABC[0:4]});
143        $for N in range(4, NR, 4):
144          vst1_bf16(c${M} + ${N}, vout${M}x${ABC[N:N+4]});
145        c${M} = (bfloat16_t*) ((uintptr_t) c${M} + cn_stride);
146
147      $for M in range(MR):
148        a${M} = (const bfloat16_t*) ((uintptr_t) a${M} - kc);
149
150      nc -= ${NR};
151    } else {
152      $for LOG2N in reversed(range(NR.bit_length())):
153        $if NR != 1 << LOG2N:
154          if (nc & ${1 << LOG2N}) {
155            $if LOG2N >= 2:
156              $for N in range(0, 1 << LOG2N, 4):
157                $for M in range(MR):
158                  vst1_bf16(c${M}, vout${M}x${ABC[N:N+4]}); c${M} += 4;
159
160              $for M in range(MR):
161                $for N in range(0, 1 << (LOG2N - 1), 4):
162                  vout${M}x${ABC[N:N+4]} = vout${M}x${ABC[N + (1 << LOG2N):N + (1 << LOG2N)+4]};
163            $elif LOG2N == 1:
164              $for M in range(MR):
165                vst1_lane_u32((void*) c${M}, vreinterpret_u32_bf16(vout${M}x${ABC[0:4]}), 0); c${M} += 2;
166
167              $for M in range(MR):
168                vout${M}x${ABC[0:4]} = vreinterpret_bf16_u16(vext_u16(vreinterpret_u16_bf16(vout${M}x${ABC[0:4]}), vreinterpret_u16_bf16(vout${M}x${ABC[0:4]}), 2));
169            $elif LOG2N == 0:
170              $for M in range(MR):
171                vst1_lane_bf16(c${M}, vout${M}x${ABC[0:4]}, 0);
172          }
173
174      nc = 0;
175    }
176  } while (nc != 0);
177}
178