KleidiAI Coverage Report


Directory: ./
File: kai/ukernels/matmul/matmul_clamp_f32_qai8dxp_qsi8cxp/kai_matmul_clamp_f32_qai8dxp1vlx4_qsi8cxp4vlx4_1vlx4vl_sme_mopa.c
Date: 2025-10-20 13:18:31
Coverage Exec Excl Total
Lines: 100.0% 63 8 71
Functions: 100.0% 14 0 14
Branches: -% 0 16 16

Line Branch Exec Source
1 //
2 // SPDX-FileCopyrightText: Copyright 2025 Arm Limited and/or its affiliates <open-source-office@arm.com>
3 //
4 // SPDX-License-Identifier: Apache-2.0
5 //
6
7 #if (!defined(__aarch64__) || !defined(__ARM_FEATURE_SVE2)) && !defined(_M_ARM64)
8 #error "This file must be compiled for AArch64, FEAT_SVE2"
9 #else // Architectural features check.
10
11 #include "kai_matmul_clamp_f32_qai8dxp1vlx4_qsi8cxp4vlx4_1vlx4vl_sme_mopa.h"
12
13 #include <stddef.h>
14
15 #include "kai/kai_common.h"
16
17 typedef struct {
18 float* dst; // 0
19 const void* lhs_packed; // 0x8
20 const void* rhs_packed; // 0x10
21 size_t dst_stride_row; // 0x18
22 size_t m; // 0x20
23 size_t n; // 0x28
24 size_t lhs_stride; // 0x30
25 size_t rhs_stride; // 0x38
26 size_t rhs_row_bytes; // 0x40
27 size_t m_blk; // 0x48
28 size_t dst_inc; // 0x50
29 float clamp_min; // 0x58
30 float clamp_max; // 0x5c
31 } KernelArgs;
32
33 void kai_kernel_matmul_clamp_f32_qai8dxp1vlx4_qsi8cxp4vlx4_1vlx4vl_sme_mopa(KernelArgs* args_ptr);
34
35 // Compute args
36 static const size_t kai_m_step = 1; // multiple of vector length
37 static const size_t kai_n_step = 4; // multiple of vector length
38 // Packing args
39 static const size_t kai_mr = 1; // multiple of vector length
40 static const size_t kai_nr = 4; // multiple of vector length
41 static const size_t kai_kr = 4;
42 static const size_t kai_sr = 1;
43 // LHS format args (num. bytes per value, multiplier, zero_point (if asymmetric))
44 static const size_t kai_num_bytes_qvalue_lhs = 1;
45 static const size_t kai_num_bytes_multiplier_lhs = 4;
46 static const size_t kai_num_bytes_zp_lhs = 4;
47 // RHS format args (num. bytes per value, multiplier, zero_point (if asymmetric), and reduction sum (if LHS is
48 // asymmetric))
49 static const size_t kai_num_bytes_qvalue_rhs = 1;
50 static const size_t kai_num_bytes_multiplier_rhs = 4;
51 static const size_t kai_num_bytes_rsum_rhs = 4;
52 // DST format args
53 static const size_t kai_num_bytes_dst_value = 4;
54 // Extra args
55 static const size_t kai_num_bytes_bias = 4;
56 static const size_t kai_k_multiple_of = 32;
57
58 927 inline static size_t kai_k_roundedup(size_t k) {
59 // Round up k to be a multiple of 32.
60 927 return kai_roundup(k, kai_k_multiple_of);
61 }
62
63 386 inline static size_t kai_get_lhs_packed_stride(size_t k) {
64 386 const size_t k_internal = kai_k_roundedup(k);
65 KAI_ASSERT((k_internal % kai_k_multiple_of) == 0);
66 386 const size_t mr = kai_get_mr_matmul_clamp_f32_qai8dxp1vlx4_qsi8cxp4vlx4_1vlx4vl_sme_mopa();
67 386 size_t lhs_packed_stride = mr * ((k_internal * kai_num_bytes_qvalue_lhs) + kai_num_bytes_multiplier_lhs);
68 // Since the LHS matrix is asymmetric with per-row quantization, we must include the
69 // the number of bytes to hold the zero point value
70 386 lhs_packed_stride += mr * kai_num_bytes_zp_lhs;
71
72 772 return lhs_packed_stride;
73 386 }
74
75 386 inline static size_t kai_get_rhs_packed_stride(size_t k) {
76 386 const size_t k_internal = kai_k_roundedup(k);
77 KAI_ASSERT((k_internal % kai_k_multiple_of) == 0);
78 386 const size_t nr = kai_get_nr_matmul_clamp_f32_qai8dxp1vlx4_qsi8cxp4vlx4_1vlx4vl_sme_mopa();
79 386 size_t rhs_packed_stride = nr * (k_internal * kai_num_bytes_qvalue_rhs);
80 386 rhs_packed_stride += nr * kai_num_bytes_multiplier_rhs;
81 // Since the LHS matrix is quantized asymmetric with per-row quantization, we also include
82 // the number of bytes for the reduction sum
83 386 rhs_packed_stride += nr * kai_num_bytes_rsum_rhs;
84 // Since the bias is packed with the RHS matrix, the stride is adjusted with the number of bytes of the bias
85 386 rhs_packed_stride += nr * kai_num_bytes_bias;
86
87 772 return rhs_packed_stride;
88 386 }
89
90 616 size_t kai_get_m_step_matmul_clamp_f32_qai8dxp1vlx4_qsi8cxp4vlx4_1vlx4vl_sme_mopa(void) {
91 616 return kai_m_step * kai_get_sme_vector_length_u8() / kai_kr;
92 }
93
94 616 size_t kai_get_n_step_matmul_clamp_f32_qai8dxp1vlx4_qsi8cxp4vlx4_1vlx4vl_sme_mopa(void) {
95 616 return kai_n_step * kai_get_sme_vector_length_u8() / kai_kr;
96 }
97
98 1003 size_t kai_get_mr_matmul_clamp_f32_qai8dxp1vlx4_qsi8cxp4vlx4_1vlx4vl_sme_mopa(void) {
99 1003 return kai_mr * kai_get_sme_vector_length_u8() / kai_kr;
100 }
101
102 1003 size_t kai_get_nr_matmul_clamp_f32_qai8dxp1vlx4_qsi8cxp4vlx4_1vlx4vl_sme_mopa(void) {
103 1003 return kai_nr * kai_get_sme_vector_length_u8() / kai_kr;
104 }
105
106 308 size_t kai_get_kr_matmul_clamp_f32_qai8dxp1vlx4_qsi8cxp4vlx4_1vlx4vl_sme_mopa(void) {
107 308 return kai_kr;
108 }
109
110 308 size_t kai_get_sr_matmul_clamp_f32_qai8dxp1vlx4_qsi8cxp4vlx4_1vlx4vl_sme_mopa(void) {
111 308 return kai_sr;
112 }
113
114 231 size_t kai_get_lhs_packed_offset_matmul_clamp_f32_qai8dxp1vlx4_qsi8cxp4vlx4_1vlx4vl_sme_mopa(size_t m_idx, size_t k) {
115 KAI_ASSERT((m_idx % kai_get_m_step_matmul_clamp_f32_qai8dxp1vlx4_qsi8cxp4vlx4_1vlx4vl_sme_mopa()) == 0);
116
117 231 const size_t mr = kai_get_mr_matmul_clamp_f32_qai8dxp1vlx4_qsi8cxp4vlx4_1vlx4vl_sme_mopa();
118
119 462 return (m_idx / mr) * kai_get_lhs_packed_stride(k);
120 231 }
121
122 231 size_t kai_get_rhs_packed_offset_matmul_clamp_f32_qai8dxp1vlx4_qsi8cxp4vlx4_1vlx4vl_sme_mopa(size_t n_idx, size_t k) {
123 KAI_ASSERT((n_idx % kai_get_n_step_matmul_clamp_f32_qai8dxp1vlx4_qsi8cxp4vlx4_1vlx4vl_sme_mopa()) == 0);
124
125 231 const size_t nr = kai_get_nr_matmul_clamp_f32_qai8dxp1vlx4_qsi8cxp4vlx4_1vlx4vl_sme_mopa();
126
127 462 return (n_idx / nr) * kai_get_rhs_packed_stride(k);
128 231 }
129
130 154 size_t kai_get_dst_offset_matmul_clamp_f32_qai8dxp1vlx4_qsi8cxp4vlx4_1vlx4vl_sme_mopa(
131 size_t m_idx, size_t n_idx, size_t dst_stride) {
132 KAI_ASSERT((m_idx % kai_get_m_step_matmul_clamp_f32_qai8dxp1vlx4_qsi8cxp4vlx4_1vlx4vl_sme_mopa()) == 0);
133 KAI_ASSERT((n_idx % kai_get_n_step_matmul_clamp_f32_qai8dxp1vlx4_qsi8cxp4vlx4_1vlx4vl_sme_mopa()) == 0);
134
135 154 return ((n_idx * kai_num_bytes_dst_value) + m_idx * dst_stride);
136 }
137
138 154 size_t kai_get_dst_size_matmul_clamp_f32_qai8dxp1vlx4_qsi8cxp4vlx4_1vlx4vl_sme_mopa(size_t m, size_t n) {
139 154 return (m * n * kai_num_bytes_dst_value);
140 }
141
142 155 void kai_run_matmul_clamp_f32_qai8dxp1vlx4_qsi8cxp4vlx4_1vlx4vl_sme_mopa(
143 size_t m, //
144 size_t n, //
145 size_t k, //
146 const void* restrict lhs_packed, //
147 const void* restrict rhs_packed, //
148 float* restrict dst, // NOLINT(readability-non-const-parameter)
149 size_t dst_stride_row, //
150 size_t dst_stride_col, //
151 float scalar_min, //
152 float scalar_max) {
153 155 KAI_UNUSED(dst_stride_col);
154 KAI_ASSERT(n > 0);
155 KAI_ASSERT(m > 0);
156
157 155 const size_t mr = kai_get_mr_matmul_clamp_f32_qai8dxp1vlx4_qsi8cxp4vlx4_1vlx4vl_sme_mopa();
158 155 const size_t nr = kai_get_nr_matmul_clamp_f32_qai8dxp1vlx4_qsi8cxp4vlx4_1vlx4vl_sme_mopa();
159
160 155 KernelArgs args;
161 155 const size_t k_internal = kai_k_roundedup(k);
162 155 args.dst = dst;
163 155 args.lhs_packed = lhs_packed;
164 155 args.rhs_packed = rhs_packed;
165 155 args.dst_stride_row = dst_stride_row;
166 155 args.m = m;
167 155 args.n = n;
168 155 args.lhs_stride = kai_get_lhs_packed_stride(k);
169 155 args.rhs_stride = kai_get_rhs_packed_stride(k);
170 155 args.rhs_row_bytes = nr * k_internal;
171 155 args.m_blk = mr * k_internal;
172 155 args.dst_inc = mr * dst_stride_row;
173 155 args.clamp_min = scalar_min;
174 155 args.clamp_max = scalar_max;
175
176 155 kai_kernel_matmul_clamp_f32_qai8dxp1vlx4_qsi8cxp4vlx4_1vlx4vl_sme_mopa(&args);
177 155 }
178
179 #endif // Architectural feature check
180