CUDA 13.2 samples update (#432)

- Added Python samples for CUDA Python 1.0 release
- Renamed top-level `Samples` directory to `cpp` to accommodate Python samples.

cpp/0_Introduction/cudaOpenMP/.vscode/c_cpp_properties.json

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+{
+    "configurations": [
+        {
+            "name": "Linux",
+            "includePath": [
+                "${workspaceFolder}/**",
+                "${workspaceFolder}/../../../Common"
+            ],
+            "defines": [],
+            "compilerPath": "/usr/local/cuda/bin/nvcc",
+            "cStandard": "gnu17",
+            "cppStandard": "gnu++14",
+            "intelliSenseMode": "linux-gcc-x64",
+            "configurationProvider": "ms-vscode.makefile-tools"
+        }
+    ],
+    "version": 4
+}

cpp/0_Introduction/cudaOpenMP/.vscode/extensions.json

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+{
+    "recommendations": [
+        "nvidia.nsight-vscode-edition",
+        "ms-vscode.cpptools",
+        "ms-vscode.makefile-tools"
+    ]
+}

cpp/0_Introduction/cudaOpenMP/CMakeLists.txt

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+cmake_minimum_required(VERSION 3.20)
+
+list(APPEND CMAKE_MODULE_PATH "${CMAKE_CURRENT_SOURCE_DIR}/../../../cmake/Modules")
+
+project(cudaOpenMP LANGUAGES C CXX CUDA)
+
+find_package(CUDAToolkit REQUIRED)
+
+set(CMAKE_POSITION_INDEPENDENT_CODE ON)
+
+set(CMAKE_CUDA_ARCHITECTURES 75 80 86 87 89 90 100 110 120)
+set(CMAKE_CUDA_FLAGS "${CMAKE_CUDA_FLAGS} -Wno-deprecated-gpu-targets")
+if(ENABLE_CUDA_DEBUG)
+    set(CMAKE_CUDA_FLAGS "${CMAKE_CUDA_FLAGS} -G")        # enable cuda-gdb (may significantly affect performance on some targets)
+else()
+    set(CMAKE_CUDA_FLAGS "${CMAKE_CUDA_FLAGS} -lineinfo") # add line information to all builds for debug tools (exclusive to -G option)
+endif()
+
+# Include directories and libraries
+include_directories(../../../Common)
+
+find_package(OpenMP)
+
+# Source file
+if(OpenMP_CXX_FOUND)
+# Add target for asyncAPI
+    add_executable(cudaOpenMP cudaOpenMP.cu)
+
+target_compile_options(cudaOpenMP PRIVATE $<$<COMPILE_LANGUAGE:CUDA>:--extended-lambda>)
+
+target_compile_features(cudaOpenMP PRIVATE cxx_std_17 cuda_std_17)
+
+    set_target_properties(cudaOpenMP PROPERTIES CUDA_SEPARABLE_COMPILATION ON)
+    target_link_libraries(cudaOpenMP PUBLIC
+        OpenMP::OpenMP_CXX
+    )
+else()
+    message(STATUS "OpenMP not found - will not build sample 'cudaOpenMP'")
+endif()
+
+# Include installation configuration
+include(${CMAKE_CURRENT_SOURCE_DIR}/../../../cmake/InstallSamples.cmake)
+setup_samples_install()

cpp/0_Introduction/cudaOpenMP/README.md

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+# cudaOpenMP - cudaOpenMP
+
+## Description
+
+This sample demonstrates how to use OpenMP API to write an application for multiple GPUs.
+
+## Key Concepts
+
+CUDA Systems Integration, OpenMP, Multithreading
+
+## Supported SM Architectures
+
+[SM 5.0 ](https://developer.nvidia.com/cuda-gpus)  [SM 5.2 ](https://developer.nvidia.com/cuda-gpus)  [SM 5.3 ](https://developer.nvidia.com/cuda-gpus)  [SM 6.0 ](https://developer.nvidia.com/cuda-gpus)  [SM 6.1 ](https://developer.nvidia.com/cuda-gpus)  [SM 7.0 ](https://developer.nvidia.com/cuda-gpus)  [SM 7.2 ](https://developer.nvidia.com/cuda-gpus)  [SM 7.5 ](https://developer.nvidia.com/cuda-gpus)  [SM 8.0 ](https://developer.nvidia.com/cuda-gpus)  [SM 8.6 ](https://developer.nvidia.com/cuda-gpus)  [SM 8.7 ](https://developer.nvidia.com/cuda-gpus)  [SM 8.9 ](https://developer.nvidia.com/cuda-gpus)  [SM 9.0 ](https://developer.nvidia.com/cuda-gpus)
+
+## Supported OSes
+
+Linux, Windows
+
+## Supported CPU Architecture
+
+x86_64, armv7l
+
+## CUDA APIs involved
+
+### [CUDA Runtime API](http://docs.nvidia.com/cuda/cuda-runtime-api/index.html)
+cudaMemcpy, cudaGetErrorString, cudaFree, cudaGetLastError, cudaSetDevice, cudaGetDeviceCount, cudaGetDevice, cudaMemset, cudaMalloc, cudaGetDeviceProperties
+
+## Dependencies needed to build/run
+[OpenMP](../../../README.md#openmp)
+
+## Prerequisites
+
+Download and install the [CUDA Toolkit](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
+Make sure the dependencies mentioned in [Dependencies]() section above are installed.
+
+## References (for more details)

cpp/0_Introduction/cudaOpenMP/cudaOpenMP.cu

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+/* Copyright (c) 2022, NVIDIA CORPORATION. All rights reserved.
+ *
+ * Redistribution and use in source and binary forms, with or without
+ * modification, are permitted provided that the following conditions
+ * are met:
+ *  * Redistributions of source code must retain the above copyright
+ *    notice, this list of conditions and the following disclaimer.
+ *  * Redistributions in binary form must reproduce the above copyright
+ *    notice, this list of conditions and the following disclaimer in the
+ *    documentation and/or other materials provided with the distribution.
+ *  * Neither the name of NVIDIA CORPORATION nor the names of its
+ *    contributors may be used to endorse or promote products derived
+ *    from this software without specific prior written permission.
+ *
+ * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
+ * EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+ * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
+ * PURPOSE ARE DISCLAIMED.  IN NO EVENT SHALL THE COPYRIGHT OWNER OR
+ * CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
+ * EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
+ * PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
+ * PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
+ * OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
+ * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+ * OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+ */
+
+/*
+ * Multi-GPU sample using OpenMP for threading on the CPU side
+ * needs a compiler that supports OpenMP 2.0
+ */
+
+#include <helper_cuda.h>
+#include <omp.h>
+#include <stdio.h> // stdio functions are used since C++ streams aren't necessarily thread safe
+
+using namespace std;
+
+// a simple kernel that simply increments each array element by b
+__global__ void kernelAddConstant(int *g_a, const int b)
+{
+    int idx = blockIdx.x * blockDim.x + threadIdx.x;
+    g_a[idx] += b;
+}
+
+// a predicate that checks whether each array element is set to its index plus b
+int correctResult(int *data, const int n, const int b)
+{
+    for (int i = 0; i < n; i++)
+        if (data[i] != i + b)
+            return 0;
+
+    return 1;
+}
+
+int main(int argc, char *argv[])
+{
+    int num_gpus = 0; // number of CUDA GPUs
+
+    printf("%s Starting...\n\n", argv[0]);
+
+    /////////////////////////////////////////////////////////////////
+    // determine the number of CUDA capable GPUs
+    //
+    cudaGetDeviceCount(&num_gpus);
+
+    if (num_gpus < 1) {
+        printf("no CUDA capable devices were detected\n");
+        return 1;
+    }
+
+    /////////////////////////////////////////////////////////////////
+    // display CPU and GPU configuration
+    //
+    printf("number of host CPUs:\t%d\n", omp_get_num_procs());
+    printf("number of CUDA devices:\t%d\n", num_gpus);
+
+    for (int i = 0; i < num_gpus; i++) {
+        cudaDeviceProp dprop;
+        cudaGetDeviceProperties(&dprop, i);
+        printf("   %d: %s\n", i, dprop.name);
+    }
+
+    printf("---------------------------\n");
+
+    /////////////////////////////////////////////////////////////////
+    // initialize data
+    //
+    unsigned int n      = num_gpus * 8192;
+    unsigned int nbytes = n * sizeof(int);
+    int         *a      = 0; // pointer to data on the CPU
+    int          b      = 3; // value by which the array is incremented
+    a                   = (int *)malloc(nbytes);
+
+    if (0 == a) {
+        printf("couldn't allocate CPU memory\n");
+        return 1;
+    }
+
+    for (unsigned int i = 0; i < n; i++)
+        a[i] = i;
+
+    ////////////////////////////////////////////////////////////////
+    // run as many CPU threads as there are CUDA devices
+    //   each CPU thread controls a different device, processing its
+    //   portion of the data.  It's possible to use more CPU threads
+    //   than there are CUDA devices, in which case several CPU
+    //   threads will be allocating resources and launching kernels
+    //   on the same device.  For example, try omp_set_num_threads(2*num_gpus);
+    //   Recall that all variables declared inside an "omp parallel" scope are
+    //   local to each CPU thread
+    //
+    omp_set_num_threads(num_gpus); // create as many CPU threads as there are CUDA devices
+// omp_set_num_threads(2*num_gpus);// create twice as many CPU threads as there
+// are CUDA devices
+#pragma omp parallel
+    {
+        unsigned int cpu_thread_id   = omp_get_thread_num();
+        unsigned int num_cpu_threads = omp_get_num_threads();
+
+        // set and check the CUDA device for this CPU thread
+        int gpu_id = -1;
+        checkCudaErrors(
+            cudaSetDevice(cpu_thread_id % num_gpus)); // "% num_gpus" allows more CPU threads than GPU devices
+        checkCudaErrors(cudaGetDevice(&gpu_id));
+        printf("CPU thread %d (of %d) uses CUDA device %d\n", cpu_thread_id, num_cpu_threads, gpu_id);
+
+        int         *d_a   = 0; // pointer to memory on the device associated with this CPU thread
+        int         *sub_a = a + cpu_thread_id * n / num_cpu_threads; // pointer to this CPU thread's portion of data
+        unsigned int nbytes_per_kernel = nbytes / num_cpu_threads;
+        dim3         gpu_threads(128); // 128 threads per block
+        dim3         gpu_blocks(n / (gpu_threads.x * num_cpu_threads));
+
+        checkCudaErrors(cudaMalloc((void **)&d_a, nbytes_per_kernel));
+        checkCudaErrors(cudaMemset(d_a, 0, nbytes_per_kernel));
+        checkCudaErrors(cudaMemcpy(d_a, sub_a, nbytes_per_kernel, cudaMemcpyHostToDevice));
+        kernelAddConstant<<<gpu_blocks, gpu_threads>>>(d_a, b);
+
+        checkCudaErrors(cudaMemcpy(sub_a, d_a, nbytes_per_kernel, cudaMemcpyDeviceToHost));
+        checkCudaErrors(cudaFree(d_a));
+    }
+    printf("---------------------------\n");
+
+    if (cudaSuccess != cudaGetLastError())
+        printf("%s\n", cudaGetErrorString(cudaGetLastError()));
+
+    ////////////////////////////////////////////////////////////////
+    // check the result
+    //
+    bool bResult = correctResult(a, n, b);
+
+    if (a)
+        free(a); // free CPU memory
+
+    exit(bResult ? EXIT_SUCCESS : EXIT_FAILURE);
+}