From 99311bc98ff51f0853a0f0a23a24fd26c5b5037b Mon Sep 17 00:00:00 2001 From: Aaron Teo Date: Sat, 6 Sep 2025 22:06:06 +0800 Subject: [PATCH] ggml-zdnn: clean up matmul codepath Signed-off-by: Aaron Teo --- ggml/src/ggml-zdnn/ggml-zdnn.cpp | 37 +++----------------------------- 1 file changed, 3 insertions(+), 34 deletions(-) diff --git a/ggml/src/ggml-zdnn/ggml-zdnn.cpp b/ggml/src/ggml-zdnn/ggml-zdnn.cpp index 6fa9f7515e..e73639a588 100644 --- a/ggml/src/ggml-zdnn/ggml-zdnn.cpp +++ b/ggml/src/ggml-zdnn/ggml-zdnn.cpp @@ -160,19 +160,6 @@ static void ggml_zdnn_mul_mat_op(ggml_backend_zdnn_context * ctx, const ggml_ten } static void ggml_zdnn_mul_mat_dispatch(ggml_backend_zdnn_context * ctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) { - bool use_mul_mat_vec = - (src0->type == GGML_TYPE_F16 || src0->type == GGML_TYPE_F16) - && src1->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32 - && src0->ne[0] % 2 == 0 && src1->ne[1] == 1; - - bool use_mul_mat_vec_q = - ggml_is_quantized(src0->type) - && src1->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32; - - bool use_mul_mat_q = - ggml_is_quantized(src0->type) - && src1->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32; - // debug helpers // GGML_LOG_INFO("%s: use_mul_mat_vec = %d\n", __func__, use_mul_mat_vec); // GGML_LOG_INFO("%s: use_mul_mat_vec_q = %d\n", __func__, use_mul_mat_vec_q); @@ -184,25 +171,7 @@ static void ggml_zdnn_mul_mat_dispatch(ggml_backend_zdnn_context * ctx, const gg // GGML_LOG_INFO("%s: src0 is contiguous %d, transposed %d, type = %s, name = %s\n", __func__, ggml_is_contiguous(src0), ggml_is_transposed(src0), ggml_type_name(src0->type), src0->name); // GGML_LOG_INFO("%s: src1 is contiguous %d, transposed %d, type = %s, name = %s\n", __func__, ggml_is_contiguous(src1), ggml_is_transposed(src1), ggml_type_name(src1->type), src1->name); - if (src0->type == GGML_TYPE_F16 && src1->type == GGML_TYPE_F16 - && !ggml_is_transposed(src0) && !ggml_is_transposed(src1) - && src1->ne[2] * src1->ne[3] > 1) { - // general KQ + KQV multi-batch - GGML_LOG_INFO("%s: using zdnn_mul_mat_batched for KQ + KQV multi-batch\n", __func__); - // ggml_zdnn_mul_mat_batched(ctx, src0, src1, dst); - } else if (use_mul_mat_vec) { - GGML_LOG_INFO("%s: using zdnn_op_mul_mat_vec for vector multiplication\n", __func__); - // ggml_zdnn_op_mul_mat(ctx, src0, src1, dst, ggml_zdnn_op_mul_mat_vec, nullptr); - } else if (use_mul_mat_vec_q) { - GGML_LOG_INFO("%s: using zdnn_op_mul_mat_vec_q for quantized vector multiplication\n", __func__); - // ggml_zdnn_op_mul_mat(ctx, src0, src1, dst, ggml_zdnn_op_mul_mat_vec_q, ggml_zdnn_quantize_row_q8_1); - } else if (use_mul_mat_q) { - GGML_LOG_INFO("%s: using zdnn_op_mul_mat_q for quantized matrix multiplication\n", __func__); - // ggml_zdnn_op_mul_mat(ctx, src0, src1, dst, ggml_zdnn_op_mul_mat_q, ggml_zdnn_quantize_mmq_q8_1); - } else { - // GGML_LOG_INFO("%s: using zdnn_op_mul_mat for general matrix multiplication\n", __func__); - ggml_zdnn_mul_mat_op(ctx, src0, src1, dst); - } + ggml_zdnn_mul_mat_op(ctx, src0, src1, dst); } static bool ggml_zdnn_compute_forward(ggml_backend_zdnn_context * ctx, ggml_tensor * dst) { @@ -262,8 +231,8 @@ static bool ggml_zdnn_supports_op(const ggml_backend_zdnn_device_context * ctx_d const ggml_tensor * inputs = op->src[1]; const int64_t ne10 = inputs->ne[0]; - const int64_t ne0 = op->ne[0]; - const int64_t ne1 = op->ne[1]; + const int64_t ne0 = op->ne[0]; + const int64_t ne1 = op->ne[1]; const int64_t max_batch = ctx_dev->max_size;