diff --git a/numba_cuda/numba/cuda/api_util.py b/numba_cuda/numba/cuda/api_util.py
index 1b2694af7..bc5bb8e41 100644
--- a/numba_cuda/numba/cuda/api_util.py
+++ b/numba_cuda/numba/cuda/api_util.py
@@ -3,6 +3,12 @@
 
 def prepare_shape_strides_dtype(shape, strides, dtype, order):
     dtype = np.dtype(dtype)
+    if isinstance(shape, (float, np.floating)):
+        raise TypeError("shape must be an integer or tuple of integers")
+    if isinstance(shape, np.ndarray) and np.issubdtype(
+        shape.dtype, np.floating
+    ):
+        raise TypeError("shape must be an integer or tuple of integers")
     if isinstance(shape, int):
         shape = (shape,)
     if isinstance(strides, int):
diff --git a/numba_cuda/numba/cuda/cudadrv/devicearray.py b/numba_cuda/numba/cuda/cudadrv/devicearray.py
index 73180e43e..819d8a6e4 100644
--- a/numba_cuda/numba/cuda/cudadrv/devicearray.py
+++ b/numba_cuda/numba/cuda/cudadrv/devicearray.py
@@ -92,6 +92,9 @@ def __init__(self, shape, strides, dtype, stream=0, gpu_data=None):
         self._dummy = dummyarray.Array.from_desc(
             0, shape, strides, dtype.itemsize
         )
+        # confirm that all elements of shape are ints
+        if not all(isinstance(dim, (int, np.integer)) for dim in shape):
+            raise TypeError("all elements of shape must be ints")
         self.shape = tuple(shape)
         self.strides = tuple(strides)
         self.dtype = dtype
diff --git a/numba_cuda/numba/cuda/tests/cudadrv/test_cuda_ndarray.py b/numba_cuda/numba/cuda/tests/cudadrv/test_cuda_ndarray.py
index ebeb1e8cd..398211d6a 100644
--- a/numba_cuda/numba/cuda/tests/cudadrv/test_cuda_ndarray.py
+++ b/numba_cuda/numba/cuda/tests/cudadrv/test_cuda_ndarray.py
@@ -45,6 +45,39 @@ def test_devicearray_shape(self):
         self.assertEqual(ary.shape, dary.shape)
         self.assertEqual(ary.shape[1:], dary.shape[1:])
 
+    def test_device_array_float(self):
+        # Ensure that a float shape raises an TypeError
+        with self.assertRaises(TypeError):
+            cuda.device_array(shape=1.23)
+        with self.assertRaises(TypeError):
+            cuda.device_array(shape=np.float64(1.23))
+        with self.assertRaises(TypeError):
+            cuda.device_array(shape=np.array(1.23))
+
+    def test_device_array_float_vectors(self):
+        # Ensure that np.array, list or tuple inputs with
+        # non-ints raise an TypeError
+        with self.assertRaises(TypeError):
+            cuda.device_array(shape=np.array([1.1]))
+        with self.assertRaises(TypeError):
+            cuda.device_array(shape=[1.1])
+        with self.assertRaises(TypeError):
+            cuda.device_array(shape=(1.1,))
+        with self.assertRaises(TypeError):
+            cuda.device_array(shape=np.array([1.1, 2.2]))
+        with self.assertRaises(TypeError):
+            cuda.device_array(shape=[1.1, 2.2])
+        with self.assertRaises(TypeError):
+            cuda.device_array(shape=(1.1, 2.2))
+
+    def test_device_array_vectors(self):
+        # Ensure that np.array or list of inputs with
+        # ints still work
+        dary = cuda.device_array(shape=np.array([10, 10]), dtype=np.bool)
+        self.assertEqual(dary.shape, (10, 10))
+        dary = cuda.device_array(shape=[10, 10], dtype=np.bool)
+        self.assertEqual(dary.shape, (10, 10))
+
     def test_devicearray(self):
         array = np.arange(100, dtype=np.int32)
         original = array.copy()