Release v13.3 of the CUDA samples with CUDA 13.3 Toolkit (#435)

This is the release of the CUDA 13.3 samples, which include additions for CUDA Tile C++, and updated CCCL and Python samples.

python/2_CoreConcepts/tmaTensorMap/README.md

@@ -73,8 +73,8 @@ The sample:
 - CUDA Toolkit 13.0 or newer with libcudacxx (cccl) headers
 - Python 3.10 or newer
 - `cuda-python` (>=13.0.0)
-- `cuda-core` (>=0.6.0)
-- `cupy-cuda13x` (>=13.0.0)
+- `cuda-core` (>=1.0.0)
+- `cupy-cuda13x` (>=14.0.0)
 
 ## Installation
 
@@ -88,8 +88,8 @@ pip install -r requirements.txt
 The `requirements.txt` installs:
 
 - `cuda-python` (>=13.0.0)
-- `cuda-core` (>=0.6.0)
-- `cupy-cuda13x` (>=13.0.0)
+- `cuda-core` (>=1.0.0)
+- `cupy-cuda13x` (>=14.0.0)
 
 ## How to Run
 

python/2_CoreConcepts/tmaTensorMap/requirements.txt

@@ -1,4 +1,4 @@
 cuda-python>=13.0.0
-cuda-core>=0.6.0
-cupy-cuda13x>=13.0.0
+cuda-core>=1.0.0
+cupy-cuda13x>=14.0.0
 numpy>=1.24.0

python/2_CoreConcepts/tmaTensorMap/tmaTensorMap.py

@@ -64,9 +64,9 @@ try:
         LaunchConfig,
         Program,
         ProgramOptions,
-        StridedMemoryView,
         launch,
     )
+    from cuda.core.utils import StridedMemoryView
     from cuda.pathfinder import find_nvidia_header_directory, get_cuda_path_or_home
     from cuda_samples_utils import print_gpu_info
 except ImportError as e:
@@ -147,11 +147,7 @@ def _get_cccl_include_paths() -> list:
     # CUDA runtime headers - needed for the CUtensorMap driver type.
     try:
         cudart_dir = find_nvidia_header_directory("cudart")
-        if (
-            cudart_dir
-            and os.path.isdir(cudart_dir)
-            and cudart_dir not in include_path
-        ):
+        if cudart_dir and os.path.isdir(cudart_dir) and cudart_dir not in include_path:
             include_path.append(cudart_dir)
     except Exception:  # noqa: S110 - fallback probes continue below
         pass
@@ -232,9 +228,9 @@ def main() -> int:
     output = cp.zeros(n, dtype=cp.float32)
     dev.sync()  # CuPy uses its own stream
 
-    tensor_map = StridedMemoryView.from_any_interface(
-        src, stream_ptr=-1
-    ).as_tensor_map(box_dim=(TILE_SIZE,))
+    tensor_map = StridedMemoryView.from_any_interface(src, stream_ptr=-1).as_tensor_map(
+        box_dim=(TILE_SIZE,)
+    )
 
     n_tiles = n // TILE_SIZE
     config = LaunchConfig(grid=n_tiles, block=TILE_SIZE)