diff --git a/nd4j/nd4j-backends/nd4j-backend-impls/nd4j-cuda/src/main/java/org/nd4j/jita/handler/impl/CudaZeroHandler.java b/nd4j/nd4j-backends/nd4j-backend-impls/nd4j-cuda/src/main/java/org/nd4j/jita/handler/impl/CudaZeroHandler.java
index 106ac9c3a..9b8c1012c 100644
--- a/nd4j/nd4j-backends/nd4j-backend-impls/nd4j-cuda/src/main/java/org/nd4j/jita/handler/impl/CudaZeroHandler.java
+++ b/nd4j/nd4j-backends/nd4j-backend-impls/nd4j-cuda/src/main/java/org/nd4j/jita/handler/impl/CudaZeroHandler.java
@@ -1180,16 +1180,23 @@ public class CudaZeroHandler implements MemoryHandler {
         return getCudaContext();
     }
 
+    //
+    private final ReentrantReadWriteLock lock = new ReentrantReadWriteLock();
 
-
-    protected synchronized cublasHandle_t getCudaCublasHandle(OpaqueLaunchContext lc) {
+    protected cublasHandle_t getCudaCublasHandle(OpaqueLaunchContext lc) {
         val deviceId = Nd4j.getAffinityManager().getDeviceForCurrentThread();
-        if (cublasHandles.get(deviceId) == null) {
-            cublasHandles.remove(deviceId);
-            cublasHandles.add(deviceId, new cublasHandle_t(nativeOps.lcBlasHandle(lc)));
-        }
+        try {
+            lock.writeLock().lock();
 
-        return cublasHandles.get(deviceId);
+            if (cublasHandles.get(deviceId) == null) {
+                cublasHandles.remove(deviceId);
+                cublasHandles.add(deviceId, new cublasHandle_t(nativeOps.lcBlasHandle(lc)));
+            }
+
+            return cublasHandles.get(deviceId);
+        } finally {
+            lock.writeLock().unlock();
+        }
     }
 
     /**
diff --git a/nd4j/nd4j-backends/nd4j-backend-impls/nd4j-native/src/main/java/org/nd4j/nativeblas/Nd4jCpu.java b/nd4j/nd4j-backends/nd4j-backend-impls/nd4j-native/src/main/java/org/nd4j/nativeblas/Nd4jCpu.java
index 8e150f618..9554a94e9 100644
--- a/nd4j/nd4j-backends/nd4j-backend-impls/nd4j-native/src/main/java/org/nd4j/nativeblas/Nd4jCpu.java
+++ b/nd4j/nd4j-backends/nd4j-backend-impls/nd4j-native/src/main/java/org/nd4j/nativeblas/Nd4jCpu.java
@@ -16985,8 +16985,20 @@ public static final int TAD_THRESHOLD = TAD_THRESHOLD();
 //         #endif
 
         /**
-         * Returns a batched matrix tensor with new batched diagonal values.
-         */
+        * Inserts elements provided by diagonal array into the main diagonal of innermost matrices of input array
+        *
+        * Input arrays:
+        *    input:    input array, considered as batch of matrices
+        *    diagonal: array containing elements to be inserted into input array,
+        *              following rank condition should be satisfied: diagonal_rank = input_rank - 1,
+        *              the shapes of diagonal and input arrays must be equal except last dimension of input array,
+        *              for example if input_shape = [A,B,C,D] then diagonal_shape = [A,B,C],
+        *              also last dimension of diagonal array should be equal to smaller of last and last but one input dimensions
+        *              that is: diagonal_shape[-1] = min(input_shape[-1], input_shape[-2])
+        *
+        * Output array:
+        *    has the same shape as input, corresponding diagonal elements are substituted
+        */
 //         #if NOT_EXCLUDED(OP_matrix_set_diag)
         @Namespace("nd4j::ops") public static class matrix_set_diag extends DeclarableOp {
             static { Loader.load(); }