mirror of
https://github.com/ggml-org/llama.cpp.git
synced 2025-11-13 10:57:15 +00:00
vulkan: fuse mul_mat_id + mul (#17095)
* vulkan: fuse mul_mat_id + mul This comes up in qwen3 moe. * split mul_mat_id fusion tests into a separate class
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@@ -830,6 +830,7 @@ struct vk_mat_vec_push_constants {
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uint32_t batch_stride_b;
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uint32_t batch_stride_d;
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uint32_t enable_bias;
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uint32_t enable_scale;
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uint32_t ne02;
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uint32_t ne12;
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uint32_t broadcast2;
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@@ -852,6 +853,7 @@ struct vk_mat_vec_id_push_constants {
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uint32_t batch_stride_b;
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uint32_t batch_stride_d;
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uint32_t enable_bias;
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uint32_t enable_scale;
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uint32_t nei0;
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uint32_t ne11;
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};
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@@ -6863,7 +6865,7 @@ static void ggml_vk_mul_mat_vec_q_f16(ggml_backend_vk_context * ctx, vk_context&
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// compute
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const vk_mat_vec_push_constants pc = {
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(uint32_t)ne00, (uint32_t)ne10, (uint32_t)ne10, (uint32_t)ne01,
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stride_batch_x, stride_batch_y, stride_batch_d, enable_bias,
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stride_batch_x, stride_batch_y, stride_batch_d, enable_bias, 0,
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(uint32_t)ne02, (uint32_t)ne12, (uint32_t)r2, (uint32_t)r3,
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};
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ggml_vk_dispatch_pipeline(ctx, subctx, dmmv,
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@@ -7684,13 +7686,22 @@ static void ggml_vk_mul_mat_vec_id_q_f16(ggml_backend_vk_context * ctx, vk_conte
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groups_x = CEIL_DIV(groups_x, groups_z);
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}
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uint32_t enable_bias = ctx->num_additional_fused_ops > 0;
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uint32_t enable_bias = 0;
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uint32_t enable_scale = 0;
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if (ctx->num_additional_fused_ops > 0) {
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if (cgraph->nodes[node_idx + 1]->op == GGML_OP_MUL) {
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enable_scale = 1;
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} else {
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GGML_ASSERT(cgraph->nodes[node_idx + 1]->op == GGML_OP_ADD_ID);
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enable_bias = 1;
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}
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}
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vk_buffer d_B = d_D;
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size_t b_buf_offset = 0;
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uint64_t b_sz = 0;
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if (enable_bias) {
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if (enable_bias || enable_scale) {
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const ggml_tensor * bias = cgraph->nodes[node_idx + 1]->src[1];
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bool b_uma = false;
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@@ -7712,7 +7723,7 @@ static void ggml_vk_mul_mat_vec_id_q_f16(ggml_backend_vk_context * ctx, vk_conte
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(uint32_t)ne00, (uint32_t)ne10, (uint32_t)ne10, (uint32_t)ne01,
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(uint32_t)x_ne, stride_batch_y, (uint32_t)(ne20*ne21),
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enable_bias,
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enable_bias, enable_scale,
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(uint32_t)nei0, (uint32_t)ne11,
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};
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@@ -12490,6 +12501,40 @@ static bool ggml_vk_can_fuse(const ggml_backend_vk_context * ctx, const struct g
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}
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}
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if (ops.size() == 2 && ops.begin()[0] == GGML_OP_MUL_MAT_ID && ops.begin()[1] == GGML_OP_MUL) {
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// additional constraints specific to this fusion
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const ggml_tensor *mmid = cgraph->nodes[node_idx];
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const ggml_tensor *mul = cgraph->nodes[node_idx + 1];
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const ggml_tensor *scale = mul->src[1];
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if (mmid != mul->src[0]) {
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return false;
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}
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// mat-vec only
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if (!ggml_vk_use_mul_mat_vec_id(cgraph, node_idx)) {
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return false;
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}
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// shaders assume the types match
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if (mmid->type != scale->type) {
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return false;
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}
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// shaders assume the bias is contiguous
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if (!ggml_is_contiguous(scale)) {
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return false;
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}
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// unaligned bias isn't handled
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if (get_misalign_bytes(ctx, scale) != 0) {
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return false;
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}
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// shader only indexes by expert index
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if (scale->ne[0] != 1 ||
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scale->ne[1] != mul->ne[1] ||
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scale->ne[2] != 1 ||
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scale->ne[3] != 1) {
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return false;
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}
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}
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return true;
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}
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@@ -12798,6 +12843,8 @@ static ggml_status ggml_backend_vk_graph_compute(ggml_backend_t backend, ggml_cg
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ctx->num_additional_fused_ops = 1;
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} else if (ggml_vk_can_fuse(ctx, cgraph, i, { GGML_OP_MUL_MAT_ID, GGML_OP_ADD_ID })) {
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ctx->num_additional_fused_ops = 1;
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} else if (ggml_vk_can_fuse(ctx, cgraph, i, { GGML_OP_MUL_MAT_ID, GGML_OP_MUL })) {
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ctx->num_additional_fused_ops = 1;
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} else if (ggml_can_fuse_subgraph(cgraph, i, { GGML_OP_RMS_NORM, GGML_OP_MUL, GGML_OP_ROPE, GGML_OP_VIEW, GGML_OP_SET_ROWS }, { i + 4 }) &&
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ggml_check_edges(cgraph, i, rms_norm_mul_rope_view_set_rows_edges) &&
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ggml_vk_can_fuse_rms_norm_mul_rope(ctx, cgraph, i) &&
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@@ -13033,7 +13080,8 @@ static void ggml_vk_graph_optimize(ggml_backend_t backend, struct ggml_cgraph *
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is_src_of(graph->nodes[j], graph->nodes[c]) &&
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!(j == c+1 && c == current_set.back() && graph->nodes[c]->op == GGML_OP_RMS_NORM && graph->nodes[j]->op == GGML_OP_MUL) &&
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!(j == c+1 && c == current_set.back() && graph->nodes[c]->op == GGML_OP_MUL_MAT && graph->nodes[j]->op == GGML_OP_ADD) &&
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!(j == c+1 && c == current_set.back() && graph->nodes[c]->op == GGML_OP_MUL_MAT_ID && graph->nodes[j]->op == GGML_OP_ADD_ID)) {
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!(j == c+1 && c == current_set.back() && graph->nodes[c]->op == GGML_OP_MUL_MAT_ID && graph->nodes[j]->op == GGML_OP_ADD_ID) &&
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!(j == c+1 && c == current_set.back() && graph->nodes[c]->op == GGML_OP_MUL_MAT_ID && graph->nodes[j]->op == GGML_OP_MUL)) {
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ok = false;
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break;
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}
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@@ -49,6 +49,7 @@ layout (push_constant) uniform parameter
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uint batch_stride_d;
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uint enable_bias;
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uint enable_scale;
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#ifdef MUL_MAT_ID
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uint nei0;
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@@ -129,6 +130,12 @@ void reduce_result(inout FLOAT_TYPE temp[NUM_COLS][NUM_ROWS], const in uint32_t
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temp[j][n] += FLOAT_TYPE(data_bias[j*p.batch_stride_d + d_offset + first_row + n]);
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#endif
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}
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#ifdef MUL_MAT_ID
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if (p.enable_scale != 0) {
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const uint expert_idx = gl_GlobalInvocationID.y;
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temp[j][n] *= FLOAT_TYPE(data_bias[expert_idx]);
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}
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#endif
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data_d[j*p.batch_stride_d + d_offset + first_row + n] = D_TYPE(temp[j][n]);
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}
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}
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@@ -171,6 +178,12 @@ void reduce_result(FLOAT_TYPE temp[NUM_COLS][NUM_ROWS], const in uint32_t d_offs
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temp[j][n] += FLOAT_TYPE(data_bias[j*p.batch_stride_d + d_offset + first_row + n]);
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#endif
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}
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#ifdef MUL_MAT_ID
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if (p.enable_scale != 0) {
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const uint expert_idx = gl_GlobalInvocationID.y;
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temp[j][n] *= FLOAT_TYPE(data_bias[expert_idx]);
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}
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#endif
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data_d[j*p.batch_stride_d + d_offset + first_row + n] = D_TYPE(temp[j][n]);
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}
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}
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@@ -203,6 +216,12 @@ void reduce_result(FLOAT_TYPE temp[NUM_COLS][NUM_ROWS], const in uint32_t d_offs
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tmpsh[j][n][0] += FLOAT_TYPE(data_bias[j*p.batch_stride_d + d_offset + first_row + n]);
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#endif
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}
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#ifdef MUL_MAT_ID
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if (p.enable_scale != 0) {
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const uint expert_idx = gl_GlobalInvocationID.y;
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tmpsh[j][n][0] *= FLOAT_TYPE(data_bias[expert_idx]);
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}
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#endif
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data_d[j*p.batch_stride_d + d_offset + first_row + n] = D_TYPE(tmpsh[j][n][0]);
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}
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}
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