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authorShouzheng Liu <61452103+lshzh-ww@users.noreply.github.com>2023-07-12 16:10:55 -0400
committerGitHub <noreply@github.com>2023-07-12 23:10:55 +0300
commit1cbf561466e957b25f0e8163c2386683f8674369 (patch)
tree4d796b3189de81bd3a32dde500d1d2f46d06eb07 /ggml-metal.metal
parent975221e9548ef6d9f4af8d39cdffc4811c050beb (diff)
metal : new q4_0 matrix-vector kernel (#2188)
Prefetch data to improve GPU utilization. ~48% faster for 33B model.
Diffstat (limited to 'ggml-metal.metal')
-rw-r--r--ggml-metal.metal103
1 files changed, 56 insertions, 47 deletions
diff --git a/ggml-metal.metal b/ggml-metal.metal
index e62fe68..30d60fa 100644
--- a/ggml-metal.metal
+++ b/ggml-metal.metal
@@ -365,6 +365,10 @@ kernel void kernel_rms_norm(
}
}
+// putting them in the kernel cause a significant performance penalty
+#define N_DST 4 // each SIMD group works on 4 rows
+#define N_SIMDGROUP 2 // number of SIMD groups in a thread group
+#define N_SIMDWIDTH 32 // assuming SIMD group size is 32
kernel void kernel_mul_mat_q4_0_f32(
device const void * src0,
device const float * src1,
@@ -372,64 +376,69 @@ kernel void kernel_mul_mat_q4_0_f32(
constant int64_t & ne00,
constant int64_t & ne10,
constant int64_t & ne0,
- threadgroup float * sum [[threadgroup(0)]],
+ constant int64_t & ne01[[buffer(4)]],
uint2 tgpig[[threadgroup_position_in_grid]],
- uint2 tpitg[[thread_position_in_threadgroup]],
- uint2 tptg[[threads_per_threadgroup]]) {
+ uint tiisg[[thread_index_in_simdgroup]],
+ uint sgitg[[simdgroup_index_in_threadgroup]]) {
const int nb = ne00/QK4_0;
-
- const int64_t r0 = tgpig.x;
- const int64_t r1 = tgpig.y;
-
- device const block_q4_0 * x = (device const block_q4_0 *) src0 + r0*nb;
+ const int r0 = tgpig.x;
+ const int r1 = tgpig.y;
+ device const block_q4_0 * x = (device const block_q4_0 *) src0 + (r0 * N_SIMDGROUP + sgitg) * N_DST * nb;
device const float * y = (device const float *) src1 + r1*ne10;
+ block_q4_0 qb_curr, qb_next;
+ float4 y_curr[8]; // src1 vector cache
+ float sumf[N_DST]={0.f}, all_sum;
+ thread float * yl=(thread float *)y_curr;
+
+ // bootstrap
+ qb_curr = x[tiisg];
+ // each thread in a SIMD group deals with 1 block.
+ for (int column = 0; column < nb / N_SIMDWIDTH; column++) {
+
+ for (int i = 0; i < QK4_0 / 4; i++) {
+ y_curr[i] = *((device float4 *)(y + N_SIMDWIDTH * (tiisg + column * QK4_0) + 4 * i));
+ }
- const int nth = tptg.x*tptg.y;
- const int ith = tptg.y*tpitg.x + tpitg.y;
-
- const int ix = tpitg.y/4; // 0 or 1
- const int iy = tpitg.y - 4*ix; // 0...3
-
- const int first = 4 * iy;
-
- float sumf = 0;
+ for (int row = 0; row < N_DST; row++) {
+ // prefetch next x block
+ qb_next = x[tiisg + ((row + 1) % N_DST) * nb + (column + ((row + 1) / N_DST)) * N_SIMDWIDTH];
- for (int i = 2*tpitg.x + ix; i < nb; i += 2*tptg.x) {
+ // calculate
+ float d = qb_curr.d;
+ float2 acc = {0.0f, 0.0f};
+ for (int i = 0; i < 16; i++) {
+ acc[0] += yl[i] * (qb_curr.qs[i] & 0xF) + yl[i+16] * (qb_curr.qs[i] >> 4);
+ acc[1] += yl[i] + yl[i+16];
+ }
+ sumf[row] += d * (acc[0] - 8.f*acc[1]);
+ qb_curr = qb_next;
+ }
+ }
- const float d = (float)x[i].d;
+ for (int i = 0; i < QK4_0 / 4; i++) {
+ y_curr[i] = *((device float4 *)(y + N_SIMDWIDTH * (tiisg + (nb / N_SIMDWIDTH) * QK4_0) + 4 * i));
+ }
- device const uint8_t * xl = x[i].qs + first;
- device const float * yl = y + i * QK4_0 + first;
+ for (int row = 0; row < N_DST; row++) {
+ // prefetch next x block
+ qb_next = x[tiisg + ((row + 1) % N_DST) * nb + (nb / N_SIMDWIDTH + ((row + 1) / N_DST)) * N_SIMDWIDTH];
+ // calculate
+ float d = qb_curr.d;
float2 acc = {0.0f, 0.0f};
-
- for (int j = 0; j < 4; ++j) {
-
- acc[0] += yl[j] * (xl[j] & 0xF) + yl[j+16] * (xl[j] >> 4);
- acc[1] += yl[j] + yl[j+16];
-
+ for (int i = 0; i < 16; i++) {
+ acc[0] += yl[i] * (qb_curr.qs[i] & 0xF) + yl[i+16] * (qb_curr.qs[i] >> 4);
+ acc[1] += yl[i] + yl[i+16];
}
+ if (tiisg < nb % N_SIMDWIDTH) {
+ sumf[row] += d * (acc[0] - 8.f*acc[1]);
+ }
+ qb_curr = qb_next;
- sumf += d * (acc[0] - 8.f*acc[1]);
- }
-
- sum[ith] = sumf;
-
- //
- // Accumulate the sum from all threads in the threadgroup
- //
- threadgroup_barrier(mem_flags::mem_threadgroup);
- if (ith%4 == 0) {
- sum[ith] += sum[ith+1] + sum[ith+2] + sum[ith+3];
- }
- threadgroup_barrier(mem_flags::mem_threadgroup);
- if (ith%16 == 0) {
- sum[ith] += sum[ith+4] + sum[ith+8] + sum[ith+12];
- }
- threadgroup_barrier(mem_flags::mem_threadgroup);
- if (ith == 0) {
- for (int i = 16; i < nth; i += 16) sum[0] += sum[i];
- dst[r1*ne0 + r0] = sum[0];
+ all_sum = simd_sum(sumf[row]);
+ if (tiisg == 0 && ((r0 * N_SIMDGROUP + sgitg) * N_DST + row) < ne01) {
+ dst[r1*ne0 + (r0 * N_SIMDGROUP + sgitg) * N_DST + row] = all_sum;
+ }
}
}