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/1_GettingStarted/copyImageArraytoGPU/README.md

@@ -39,7 +39,7 @@ Copy image arrays between CPU and GPU memory using the modern `cuda.core` API wi
 ### From `cupy`:
 
 - `cp.from_dlpack()` - Create GPU array view from DLPack capsule
-- `cp.cuda.ExternalStream()` - Use external CUDA stream
+- `cp.cuda.Stream.from_external()` - Use external CUDA stream
 
 ### From `cuda_samples_utils`:
 
@@ -58,8 +58,8 @@ Copy image arrays between CPU and GPU memory using the modern `cuda.core` API wi
 - Python 3.10 or newer
 - NumPy 2.3.2 or newer (required for DLPack support)
 - `cuda-python` package (>=13.0.0+)
-- `cuda-core` package (>=0.6.0)
-- `cupy-cuda13x` package (13.0.0+)
+- `cuda-core` package (>=1.0.0)
+- `cupy-cuda13x` package (14.0.0+)
 
 ## Installation
 
@@ -73,8 +73,8 @@ pip install -r requirements.txt
 The requirements.txt installs:
 - `numpy` (2.3.2+, required for DLPack)
 - `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/1_GettingStarted/copyImageArraytoGPU/copyImageArraytoGPU.py

@@ -195,7 +195,7 @@ def main():
     print(f"[Image array copy of {H}x{W}x{C} image]")
 
     # Step 2: Configure CuPy to use our CUDA stream (for interoperability)
-    cp.cuda.ExternalStream(int(stream.handle)).use()
+    cp.cuda.Stream.from_external(stream).use()
 
     # Step 3: Create a test image on CPU
     print("Creating sample image...")

python/1_GettingStarted/copyImageArraytoGPU/requirements.txt

@@ -2,5 +2,5 @@
 
 numpy>=2.3.2
 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