only use dmmv for supported types

ggml/src/ggml-cuda.cu

@@ -1885,7 +1885,7 @@ static void ggml_cuda_mul_mat_batched_cublas(ggml_backend_cuda_context & ctx, co
 static void ggml_cuda_mul_mat(ggml_backend_cuda_context & ctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) {
     const bool split = ggml_backend_buffer_is_cuda_split(src0->buffer);
 
-    bool use_dequantize_mul_mat_vec = (ggml_is_quantized(src0->type) || src0->type == GGML_TYPE_F16)
+    bool use_dequantize_mul_mat_vec = ggml_cuda_dmmv_type_supported(src0->type)
         && src1->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32
         && src0->ne[0] % (GGML_CUDA_DMMV_X*2) == 0 && src1->ne[1] == 1;
     bool          use_mul_mat_vec_q =  ggml_is_quantized(src0->type)

ggml/src/ggml-cuda/dmmv.cu

@@ -672,3 +672,12 @@ void ggml_cuda_op_dequantize_mul_mat_vec(
     GGML_UNUSED(src1_ncols);
     GGML_UNUSED(src1_padded_row_size);
 }
+
+bool ggml_cuda_dmmv_type_supported(ggml_type src0_type) {
+    return src0_type == GGML_TYPE_Q4_0 || src0_type == GGML_TYPE_Q4_1 ||
+        src0_type == GGML_TYPE_Q5_0 || src0_type == GGML_TYPE_Q5_1 ||
+        src0_type == GGML_TYPE_Q8_0 || src0_type == GGML_TYPE_Q2_K ||
+        src0_type == GGML_TYPE_Q3_K || src0_type == GGML_TYPE_Q4_K ||
+        src0_type == GGML_TYPE_Q5_K || src0_type == GGML_TYPE_Q6_K ||
+        src0_type == GGML_TYPE_F16;
+}

ggml/src/ggml-cuda/dmmv.cuh

@@ -16,3 +16,5 @@ void ggml_cuda_op_dequantize_mul_mat_vec(
     const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst, const char * src0_dd_i, const float * src1_ddf_i,
     const char * src1_ddq_i, float * dst_dd_i, const int64_t row_low, const int64_t row_high, const int64_t src1_ncols,
     const int64_t src1_padded_row_size, cudaStream_t stream);
+
+bool ggml_cuda_dmmv_type_supported(ggml_type src0_type);