Skip to content

Commit 2be47d4

Browse files
committed
ggml-cpu: FA add GEMM microkernel
1 parent b828e18 commit 2be47d4

4 files changed

Lines changed: 198 additions & 55 deletions

File tree

ggml/src/ggml-cpu/common.h

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -6,8 +6,8 @@
66
#include "ggml-impl.h"
77
#include "simd-mappings.h"
88

9-
#define GGML_FA_TILE_Q 32
10-
#define GGML_FA_TILE_KV 16
9+
#define GGML_FA_TILE_Q 64
10+
#define GGML_FA_TILE_KV 64
1111

1212
#ifdef __cplusplus
1313

ggml/src/ggml-cpu/ggml-cpu.c

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -2874,8 +2874,8 @@ struct ggml_cplan ggml_graph_plan(
28742874
const int64_t DV = node->src[2]->ne[0];
28752875

28762876
// Tiled flash attention scratch (tile sizes defined in common.h)
2877-
// Per-thread: Q_q + KQ + mask + VKQ32 + V32 + padding
2878-
size_t prefill = sizeof(float)*(GGML_FA_TILE_Q*DK + 2*GGML_FA_TILE_Q*GGML_FA_TILE_KV + GGML_FA_TILE_Q*DV + GGML_FA_TILE_KV*DV)*n_tasks;
2877+
// Per-thread: Q_q + KQ + mask + VKQ32 + V32 + K_f32 + padding
2878+
size_t prefill = sizeof(float)*(GGML_FA_TILE_Q*DK + 2*GGML_FA_TILE_Q*GGML_FA_TILE_KV + GGML_FA_TILE_Q*DV + GGML_FA_TILE_KV*DV + GGML_FA_TILE_KV*DK)*n_tasks;
28792879

28802880
// Decode path: n_kv_chunks = n_tasks (one chunk per thread)
28812881
// Per-thread: VKQ accmulator (DV), partial M, partial S + intra-thread scratch for V, Q and VKQ

ggml/src/ggml-cpu/ops.cpp

Lines changed: 66 additions & 51 deletions
Original file line numberDiff line numberDiff line change
@@ -3,6 +3,7 @@
33
#include "ggml-cpu.h"
44
#include "ggml-impl.h"
55
#include "binary-ops.h"
6+
#include "simd-gemm.h"
67
#include "ggml.h"
78
#include "unary-ops.h"
89
#include "vec.h"
@@ -8326,10 +8327,6 @@ static void ggml_compute_forward_flash_attn_ext_tiled(
83268327
GGML_ASSERT(k->type == v->type);
83278328
const ggml_type kv_type = k->type;
83288329

8329-
const auto * kv_type_traits_cpu = ggml_get_type_traits_cpu(kv_type);
8330-
const ggml_from_float_t kv_from_float = kv_type_traits_cpu->from_float;
8331-
const ggml_vec_dot_t kv_vec_dot = kv_type_traits_cpu->vec_dot;
8332-
const size_t kv_type_size = ggml_type_size(kv_type);
83338330

83348331
// broadcast factors
83358332
const int64_t rk2 = neq2/nek2;
@@ -8360,8 +8357,9 @@ static void ggml_compute_forward_flash_attn_ext_tiled(
83608357

83618358
static constexpr int Q_TILE_SZ = ggml_fa_tile_config::Q;
83628359
static constexpr int KV_TILE_SZ = ggml_fa_tile_config::KV;
8363-
8364-
GGML_ASSERT(nek1 % KV_TILE_SZ == 0 && "KV sequence length must be divisible by KV_TILE_SZ");
8360+
#ifdef GGML_SIMD
8361+
GGML_ASSERT(DV % GGML_F32_EPR == 0);
8362+
#endif
83658363

83668364
int ir = ir0;
83678365
while (ir < ir1) {
@@ -8389,18 +8387,20 @@ static void ggml_compute_forward_flash_attn_ext_tiled(
83898387
}
83908388

83918389
// Per-thread scratch layout:
8392-
// Q_q: Q_TILE_SZ * DK (converted Q tile in KV type)
8390+
// Q_q: Q_TILE_SZ * DK (converted Q tile — F32 for GEMM, KV type for scalar)
83938391
// KQ: Q_TILE_SZ * KV_TILE_SZ (attention scores in float)
83948392
// mask: Q_TILE_SZ * KV_TILE_SZ (mask in float)
83958393
// VKQ32: Q_TILE_SZ * DV (FP32 output accumulator)
8396-
// V32: KV_TILE_SZ * DV (F32 buffer for V tile - used for f166 conversion)
8397-
float * base = (float *) params->wdata + ith*(Q_TILE_SZ*DK + 2*Q_TILE_SZ*KV_TILE_SZ + Q_TILE_SZ*DV + KV_TILE_SZ*DV + CACHE_LINE_SIZE_F32);
8394+
// V32: KV_TILE_SZ * DV (F32 buffer for V tile)
8395+
// K_f32: KV_TILE_SZ * DK (F32 buffer for K tile — GEMM path)
8396+
float * base = (float *) params->wdata + ith*(Q_TILE_SZ*DK + 2*Q_TILE_SZ*KV_TILE_SZ + Q_TILE_SZ*DV + KV_TILE_SZ*DV + KV_TILE_SZ*DK + CACHE_LINE_SIZE_F32);
83988397

83998398
void * Q_q = base;
84008399
float * KQ = (float *)((char *)base + Q_TILE_SZ * DK * sizeof(float));
84018400
float * mask32 = KQ + Q_TILE_SZ * KV_TILE_SZ;
84028401
float * VKQ32 = mask32 + Q_TILE_SZ * KV_TILE_SZ;
8403-
float * V32 = VKQ32 + Q_TILE_SZ * DV; // F32 buffer for V tile
8402+
float * V32 = VKQ32 + Q_TILE_SZ * DV;
8403+
float * K_f32 = V32 + KV_TILE_SZ * DV;
84048404

84058405
memset(VKQ32, 0, Q_TILE_SZ * DV * sizeof(float));
84068406
memset(mask32, 0, Q_TILE_SZ * KV_TILE_SZ * sizeof(float));
@@ -8413,42 +8413,69 @@ static void ggml_compute_forward_flash_attn_ext_tiled(
84138413
const int iv3 = iq3 / rv3;
84148414
const int iv2 = iq2 / rv2;
84158415

8416-
for (int tq = 0; tq < tile_rows; tq++) {
8417-
const float * pq = (const float *) ((char *) q->data + ((iq1 + tq)*nbq1 + iq2*nbq2 + iq3*nbq3));
8418-
kv_from_float(pq, (char *)Q_q + tq * DK * kv_type_size, DK);
8419-
}
8420-
// Zero-pad remaining rows
8421-
for (int tq = tile_rows; tq < Q_TILE_SZ; tq++) {
8422-
memset((char *)Q_q + tq * DK * kv_type_size, 0, DK * kv_type_size);
8416+
{
8417+
float * Q_f32 = (float *)Q_q;
8418+
for (int tq = 0; tq < tile_rows; tq++) {
8419+
const float * pq = (const float *) ((char *) q->data + ((iq1 + tq)*nbq1 + iq2*nbq2 + iq3*nbq3));
8420+
memcpy(Q_f32 + tq * DK, pq, DK * sizeof(float));
8421+
}
8422+
for (int tq = tile_rows; tq < Q_TILE_SZ; tq++) {
8423+
memset(Q_f32 + tq * DK, 0, DK * sizeof(float));
8424+
}
84238425
}
84248426

84258427
for (int64_t ic = 0; ic < nek1; ic += KV_TILE_SZ) {
8428+
const int kv_tile = (int)std::min((int64_t)KV_TILE_SZ, nek1 - ic);
84268429

84278430
// skip the tile entirely if all the masks are -inf
84288431
if (mask) {
84298432
bool can_skip = true;
84308433
for (int tq = 0; tq < tile_rows; tq++) {
84318434
const ggml_fp16_t * mp_row = (const ggml_fp16_t *)((const char *) mask->data + (iq1 + tq)*mask->nb[1] + (iq2%mask->ne[2])*mask->nb[2] + (iq3%mask->ne[3])*mask->nb[3]);
8432-
for (int tk = 0; tk < KV_TILE_SZ; tk++) {
8435+
for (int tk = 0; tk < kv_tile; tk++) {
84338436
mask32[tq * KV_TILE_SZ + tk] = slope * GGML_CPU_FP16_TO_FP32(mp_row[ic + tk]);
84348437
if (mask32[tq * KV_TILE_SZ + tk] != -INFINITY) {
84358438
can_skip = false;
84368439
}
84378440
}
8441+
// Pad remaining mask entries with -inf
8442+
for (int tk = kv_tile; tk < KV_TILE_SZ; tk++) {
8443+
mask32[tq * KV_TILE_SZ + tk] = -INFINITY;
8444+
}
84388445
}
84398446

84408447
if (can_skip) {
84418448
continue;
84428449
}
84438450
}
84448451

8445-
for (int tq = 0; tq < Q_TILE_SZ; tq++) {
8446-
const void * q_row = (const char *)Q_q + tq * DK * kv_type_size;
8447-
for (int tk = 0; tk < KV_TILE_SZ; tk++) {
8448-
const void * k_row = (const char *) k->data + ((ic + tk)*nbk1 + ik2*nbk2 + ik3*nbk3);
8449-
float s;
8450-
kv_vec_dot(DK, &s, 0, k_row, 0, q_row, 0, 1);
8451-
KQ[tq * KV_TILE_SZ + tk] = s * scale;
8452+
// Pack K tile transposed: K_f32[dk][kv] so KV_TILE is contiguous (SIMD dim)
8453+
// Zero-pad the last tile so the GEMM always operates on KV_TILE_SZ columns
8454+
memset(K_f32, 0, DK * KV_TILE_SZ * sizeof(float));
8455+
for (int tk = 0; tk < kv_tile; tk++) {
8456+
const char * k_data = (const char *)k->data + (ic + tk)*nbk1 + ik2*nbk2 + ik3*nbk3;
8457+
if (kv_type == GGML_TYPE_F16) {
8458+
const ggml_fp16_t * k_f16 = (const ggml_fp16_t *)k_data;
8459+
for (int64_t dk = 0; dk < DK; dk++) {
8460+
K_f32[dk * KV_TILE_SZ + tk] = GGML_CPU_FP16_TO_FP32(k_f16[dk]);
8461+
}
8462+
} else {
8463+
const float * k_f32_src = (const float *)k_data;
8464+
for (int64_t dk = 0; dk < DK; dk++) {
8465+
K_f32[dk * KV_TILE_SZ + tk] = k_f32_src[dk];
8466+
}
8467+
}
8468+
}
8469+
memset(KQ, 0, Q_TILE_SZ * KV_TILE_SZ * sizeof(float));
8470+
simd_gemm(KQ, (const float *)Q_q, K_f32, Q_TILE_SZ, DK, KV_TILE_SZ);
8471+
ggml_vec_scale_f32(Q_TILE_SZ * KV_TILE_SZ, KQ, scale);
8472+
8473+
// Set padded KQ entries to -inf so softmax gives them zero weight
8474+
if (kv_tile < KV_TILE_SZ) {
8475+
for (int tq = 0; tq < Q_TILE_SZ; tq++) {
8476+
for (int tk = kv_tile; tk < KV_TILE_SZ; tk++) {
8477+
KQ[tq * KV_TILE_SZ + tk] = -INFINITY;
8478+
}
84528479
}
84538480
}
84548481

@@ -8488,33 +8515,23 @@ static void ggml_compute_forward_flash_attn_ext_tiled(
84888515
S[tq] += ggml_vec_soft_max_f32(KV_TILE_SZ, kq_row, kq_row, Mnew);
84898516
}
84908517

8491-
// Convert V tile to F32 first (if F16), then do MAD
8492-
// On x86, ggml_vec_mad_f16 internall converts F16<->F32 on every load/store, so pre-converting is faster.
8493-
// TODO: on ARM, native f16 should be faster
8494-
if (kv_type == GGML_TYPE_F16) {
8495-
for (int tk = 0; tk < KV_TILE_SZ; tk++) {
8496-
const ggml_fp16_t * v_row = (const ggml_fp16_t *)((const char *) v->data + ((ic + tk)*nbv1 + iv2*nbv2 + iv3*nbv3));
8497-
ggml_fp16_to_fp32_row(v_row, V32 + tk * DV, DV);
8498-
}
8499-
for (int tq = 0; tq < Q_TILE_SZ; tq++) {
8500-
if (skip[tq]) continue;
8501-
float * vkq_row = VKQ32 + tq * DV;
8502-
for (int tk = 0; tk < KV_TILE_SZ; tk++) {
8503-
const float p = KQ[tq * KV_TILE_SZ + tk];
8504-
ggml_vec_mad_f32(DV, vkq_row, V32 + tk * DV, p);
8505-
}
8518+
// V accumulation: VKQ32 += softmax(KQ) * V
8519+
// Pack V tile to contiguous F32, zero-padded
8520+
memset(V32, 0, KV_TILE_SZ * DV * sizeof(float));
8521+
for (int tk = 0; tk < kv_tile; tk++) {
8522+
const char * v_data = (const char *)v->data + (ic + tk)*nbv1 + iv2*nbv2 + iv3*nbv3;
8523+
if (kv_type == GGML_TYPE_F16) {
8524+
ggml_fp16_to_fp32_row((const ggml_fp16_t *)v_data, V32 + tk * DV, DV);
8525+
} else {
8526+
memcpy(V32 + tk * DV, v_data, DV * sizeof(float));
85068527
}
8507-
} else {
8508-
for (int tq = 0; tq < Q_TILE_SZ; tq++) {
8509-
if (skip[tq]) continue;
8510-
float * vkq_row = VKQ32 + tq * DV;
8511-
for (int tk = 0; tk < KV_TILE_SZ; tk++) {
8512-
const float p = KQ[tq * KV_TILE_SZ + tk];
8513-
const float * v_row = (const float *)((const char *) v->data + ((ic + tk)*nbv1 + iv2*nbv2 + iv3*nbv3));
8514-
ggml_vec_mad_f32(DV, vkq_row, v_row, p);
8515-
}
8528+
}
8529+
for (int tq = 0; tq < Q_TILE_SZ; tq++) {
8530+
if (skip[tq]) {
8531+
memset(KQ + tq * KV_TILE_SZ, 0, KV_TILE_SZ * sizeof(float));
85168532
}
85178533
}
8534+
simd_gemm(VKQ32, KQ, V32, Q_TILE_SZ, KV_TILE_SZ, DV);
85188535
}
85198536

85208537
// sinks (apply only to valid rows in the tile)
@@ -8731,13 +8748,11 @@ static void ggml_compute_forward_flash_attn_ext_f16(
87318748

87328749
const int64_t dr = (nr + nchunk - 1) / nchunk;
87338750

8734-
static constexpr int64_t KV_TILE_SZ = ggml_fa_tile_config::KV;
87358751
static constexpr int64_t Q_TILE_SZ = ggml_fa_tile_config::Q;
87368752
const bool use_tiled = !use_ref &&
87378753
(q->type == GGML_TYPE_F32 &&
87388754
kv_is_f32_or_f16 &&
87398755
k->type == v->type &&
8740-
nek1 % KV_TILE_SZ == 0 &&
87418756
neq1 >= Q_TILE_SZ);
87428757

87438758
int current_chunk = ith;

ggml/src/ggml-cpu/simd-gemm.h

Lines changed: 128 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,128 @@
1+
#pragma once
2+
3+
// Computes C[M x N] += A[M x K] * B[K x N]
4+
5+
#include "ggml-cpu-impl.h"
6+
#include "vec.h"
7+
#include "common.h"
8+
9+
#ifdef GGML_SIMD
10+
11+
// TODO: untested on avx512 and arm
12+
// These are in units of GGML_F32_EPR
13+
#if defined(__AVX512F__) || defined (__ARM_NEON__)
14+
static constexpr int GEMM_RM = 6;
15+
static constexpr int GEMM_RN = 4; // 24+4+1 = 29/32
16+
#elif defined(__AVX2__) || defined(__AVX__)
17+
static constexpr int GEMM_RM = 6;
18+
static constexpr int GEMM_RN = 2; // 12+2+1 = 15/16
19+
#else
20+
static constexpr int GEMM_RM = 2;
21+
static constexpr int GEMM_RN = 2;
22+
#endif
23+
24+
template <int RM, int RN>
25+
static inline void simd_gemm_ukernel(
26+
float * GGML_RESTRICT C,
27+
const float * GGML_RESTRICT A,
28+
const float * GGML_RESTRICT B,
29+
int64_t K, int64_t N,
30+
int ii, int64_t jj)
31+
{
32+
static constexpr int KN = GGML_F32_EPR;
33+
34+
GGML_F32_VEC acc[RM][RN];
35+
for (int i = 0; i < RM; i++) {
36+
for (int r = 0; r < RN; r++) {
37+
acc[i][r] = GGML_F32_VEC_LOAD(C + (ii + i) * N + jj + r * KN);
38+
}
39+
}
40+
41+
for (int64_t kk = 0; kk < K; kk++) {
42+
GGML_F32_VEC Bv[RN];
43+
for (int r = 0; r < RN; r++) {
44+
Bv[r] = GGML_F32_VEC_LOAD(B + kk * N + jj + r * KN);
45+
}
46+
for (int i = 0; i < RM; i++) {
47+
GGML_F32_VEC p = GGML_F32_VEC_SET1(A[(ii + i) * K + kk]);
48+
for (int r = 0; r < RN; r++) {
49+
acc[i][r] = GGML_F32_VEC_FMA(acc[i][r], Bv[r], p);
50+
}
51+
}
52+
}
53+
54+
for (int i = 0; i < RM; i++) {
55+
for (int r = 0; r < RN; r++) {
56+
GGML_F32_VEC_STORE(C + (ii + i) * N + jj + r * KN, acc[i][r]);
57+
}
58+
}
59+
}
60+
61+
// C[M x N] += A[M x K] * B[K x N]
62+
static void simd_gemm(
63+
float * GGML_RESTRICT C,
64+
const float * GGML_RESTRICT A,
65+
const float * GGML_RESTRICT B,
66+
int M, int64_t K, int64_t N)
67+
{
68+
static constexpr int KN = GGML_F32_EPR;
69+
70+
int ii = 0;
71+
for (; ii + GEMM_RM <= M; ii += GEMM_RM) {
72+
int64_t jj = 0;
73+
for (; jj + GEMM_RN * KN <= N; jj += GEMM_RN * KN) {
74+
simd_gemm_ukernel<GEMM_RM, GEMM_RN>(C, A, B, K, N, ii, jj);
75+
}
76+
for (; jj + KN <= N; jj += KN) {
77+
simd_gemm_ukernel<GEMM_RM, 1>(C, A, B, K, N, ii, jj);
78+
}
79+
for (; jj < N; jj++) {
80+
for (int i = 0; i < GEMM_RM; i++) {
81+
float a = C[(ii + i) * N + jj];
82+
for (int64_t kk = 0; kk < K; kk++) {
83+
a += A[(ii + i) * K + kk] * B[kk * N + jj];
84+
}
85+
C[(ii + i) * N + jj] = a;
86+
}
87+
}
88+
}
89+
90+
// Tail rows: one at a time
91+
for (; ii < M; ii++) {
92+
int64_t jj = 0;
93+
for (; jj + GEMM_RN * KN <= N; jj += GEMM_RN * KN) {
94+
simd_gemm_ukernel<1, GEMM_RN>(C, A, B, K, N, ii, jj);
95+
}
96+
for (; jj + KN <= N; jj += KN) {
97+
simd_gemm_ukernel<1, 1>(C, A, B, K, N, ii, jj);
98+
}
99+
for (; jj < N; jj++) {
100+
float a = C[ii * N + jj];
101+
for (int64_t kk = 0; kk < K; kk++) {
102+
a += A[ii * K + kk] * B[kk * N + jj];
103+
}
104+
C[ii * N + jj] = a;
105+
}
106+
}
107+
}
108+
109+
#else // !GGML_SIMD
110+
111+
static void simd_gemm(
112+
float * GGML_RESTRICT C,
113+
const float * GGML_RESTRICT A,
114+
const float * GGML_RESTRICT B,
115+
int M, int64_t K, int64_t N)
116+
{
117+
for (int i = 0; i < M; i++) {
118+
for (int64_t j = 0; j < N; j++) {
119+
float sum = C[i * N + j];
120+
for (int64_t kk = 0; kk < K; kk++) {
121+
sum += A[i * K + kk] * B[kk * N + j];
122+
}
123+
C[i * N + j] = sum;
124+
}
125+
}
126+
}
127+
128+
#endif // GGML_SIMD

0 commit comments

Comments
 (0)