use stride=128 if built for tensor cores

ggml-cuda.cu

@@ -467,7 +467,13 @@ static_assert(K_QUANTS_PER_ITERATION == 1 || K_QUANTS_PER_ITERATION == 2, "K_QUA
 #define GGML_CUDA_PEER_MAX_BATCH_SIZE 128
 #endif // GGML_CUDA_PEER_MAX_BATCH_SIZE
 
+#define MUL_MAT_SRC1_COL_STRIDE_MMQ 128
+
+#ifdef CUDA_USE_TENSOR_CORES
 #define MUL_MAT_SRC1_COL_STRIDE 128
+#else
+#define MUL_MAT_SRC1_COL_STRIDE 4096
+#endif
 
 #define MAX_STREAMS 8
 static cudaStream_t g_cudaStreams[GGML_CUDA_MAX_DEVICES][MAX_STREAMS] = { { nullptr } };
@@ -7158,7 +7164,10 @@ static void ggml_cuda_op_mul_mat(
         CUDA_CHECK(cudaEventRecord(src0_extra->events[g_main_device][0], g_cudaStreams[g_main_device][0]));
     }
 
-    const int64_t src1_col_stride = split && used_devices > 1 ? MUL_MAT_SRC1_COL_STRIDE : ne11;
+    const int64_t src1_col_stride = !split || used_devices == 1 ? ne11                        :
+                                    convert_src1_to_q8_1        ? MUL_MAT_SRC1_COL_STRIDE_MMQ :
+                                                                  MUL_MAT_SRC1_COL_STRIDE;
+
     for (int64_t src1_col_0 = 0; src1_col_0 < ne11; src1_col_0 += src1_col_stride) {
         const int64_t is = split ? (src1_col_0/src1_col_stride) % MAX_STREAMS : 0;
         const int64_t src1_ncols = src1_col_0 + src1_col_stride > ne11 ? ne11 - src1_col_0 : src1_col_stride;
@@ -7296,7 +7305,7 @@ static void ggml_cuda_op_mul_mat(
 
     // main device waits for all other devices to be finished
     if (split && g_device_count > 1) {
-        int64_t is_max = (ne11 + MUL_MAT_SRC1_COL_STRIDE - 1) / MUL_MAT_SRC1_COL_STRIDE;
+        int64_t is_max = (ne11 + src1_col_stride - 1) / src1_col_stride;
         is_max = is_max <= MAX_STREAMS ? is_max : MAX_STREAMS;
 
         CUDA_CHECK(ggml_cuda_set_device(g_main_device));