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/simpleZeroCopy/.vscode/c_cpp_properties.json

@@ -0,0 +1,18 @@
+{
+    "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/simpleZeroCopy/.vscode/extensions.json

@@ -0,0 +1,7 @@
+{
+    "recommendations": [
+        "nvidia.nsight-vscode-edition",
+        "ms-vscode.cpptools",
+        "ms-vscode.makefile-tools"
+    ]
+}

cpp/0_Introduction/simpleZeroCopy/CMakeLists.txt

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+cmake_minimum_required(VERSION 3.20)
+
+list(APPEND CMAKE_MODULE_PATH "${CMAKE_CURRENT_SOURCE_DIR}/../../../cmake/Modules")
+
+project(simpleZeroCopy LANGUAGES C CXX CUDA)
+
+find_package(CUDAToolkit REQUIRED)
+
+set(CMAKE_POSITION_INDEPENDENT_CODE ON)
+
+set(CMAKE_CUDA_ARCHITECTURES 75 80 86 87 89 90 100 110 120)
+set(CMAKE_CUDA_FLAGS "${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)
+
+# Source file
+# Add target for simpleZeroCopy
+add_executable(simpleZeroCopy simpleZeroCopy.cu)
+
+target_compile_options(simpleZeroCopy PRIVATE $<$<COMPILE_LANGUAGE:CUDA>:--extended-lambda>)
+
+target_compile_features(simpleZeroCopy PRIVATE cxx_std_17 cuda_std_17)
+
+set_target_properties(simpleZeroCopy PROPERTIES CUDA_SEPARABLE_COMPILATION ON)
+
+# Include installation configuration
+include(${CMAKE_CURRENT_SOURCE_DIR}/../../../cmake/InstallSamples.cmake)
+setup_samples_install()

cpp/0_Introduction/simpleZeroCopy/README.md

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+# simpleZeroCopy - simpleZeroCopy
+
+## Description
+
+This sample illustrates how to use Zero MemCopy, kernels can read and write directly to pinned system memory.
+
+## Key Concepts
+
+Performance Strategies, Pinned System Paged Memory, Vector Addition
+
+## 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)
+cudaHostAlloc, cudaSetDeviceFlags, cudaHostRegister, cudaSetDevice, cudaGetDeviceCount, cudaHostGetDevicePointer, cudaDeviceSynchronize, cudaFreeHost, cudaGetDeviceProperties, cudaHostUnregister
+
+## Prerequisites
+
+Download and install the [CUDA Toolkit](https://developer.nvidia.com/cuda-downloads) for your corresponding platform.
+
+## References (for more details)

cpp/0_Introduction/simpleZeroCopy/simpleZeroCopy.cu

@@ -0,0 +1,250 @@
+/* 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.
+ */
+
+// System includes
+#include <assert.h>
+#include <stdio.h>
+
+// CUDA runtime
+#include <cuda_runtime.h>
+
+// helper functions and utilities to work with CUDA
+#include <helper_cuda.h>
+#include <helper_functions.h>
+
+#ifndef MAX
+#define MAX(a, b) (a > b ? a : b)
+#endif
+
+/* Add two vectors on the GPU */
+__global__ void vectorAddGPU(float *a, float *b, float *c, int N)
+{
+    int idx = blockIdx.x * blockDim.x + threadIdx.x;
+
+    if (idx < N) {
+        c[idx] = a[idx] + b[idx];
+    }
+}
+
+// Allocate generic memory with malloc() and pin it laster instead of using
+// cudaHostAlloc()
+bool bPinGenericMemory = false;
+
+// Macro to aligned up to the memory size in question
+#define MEMORY_ALIGNMENT  4096
+#define ALIGN_UP(x, size) (((size_t)x + (size - 1)) & (~(size - 1)))
+
+int main(int argc, char **argv)
+{
+    int            n, nelem, deviceCount;
+    int            idev   = 0; // use default device 0
+    char          *device = NULL;
+    unsigned int   flags;
+    size_t         bytes;
+    float         *a, *b, *c;          // Pinned memory allocated on the CPU
+    float         *a_UA, *b_UA, *c_UA; // Non-4K Aligned Pinned memory on the CPU
+    float         *d_a, *d_b, *d_c;    // Device pointers for mapped memory
+    float          errorNorm, refNorm, ref, diff;
+    cudaDeviceProp deviceProp;
+
+    if (checkCmdLineFlag(argc, (const char **)argv, "help")) {
+        printf("Usage:  simpleZeroCopy [OPTION]\n\n");
+        printf("Options:\n");
+        printf("  --device=[device #]  Specify the device to be used\n");
+        printf("  --use_generic_memory (optional) use generic page-aligned for system "
+               "memory\n");
+        return EXIT_SUCCESS;
+    }
+
+    /* Get the device selected by the user or default to 0, and then set it. */
+    if (getCmdLineArgumentString(argc, (const char **)argv, "device", &device)) {
+        cudaGetDeviceCount(&deviceCount);
+        idev = atoi(device);
+
+        if (idev >= deviceCount || idev < 0) {
+            fprintf(stderr, "Device number %d is invalid, will use default CUDA device 0.\n", idev);
+            idev = 0;
+        }
+    }
+
+    // if GPU found supports SM 1.2, then continue, otherwise we exit
+    if (!checkCudaCapabilities(1, 2)) {
+        exit(EXIT_SUCCESS);
+    }
+
+    if (checkCmdLineFlag(argc, (const char **)argv, "use_generic_memory")) {
+#if defined(__APPLE__) || defined(MACOSX)
+        bPinGenericMemory = false; // Generic Pinning of System Paged memory is not
+                                   // currently supported on Mac OSX
+#else
+        bPinGenericMemory = true;
+#endif
+    }
+
+    if (bPinGenericMemory) {
+        printf("> Using Generic System Paged Memory (malloc)\n");
+    }
+    else {
+        printf("> Using CUDA Host Allocated (cudaHostAlloc)\n");
+    }
+
+    checkCudaErrors(cudaSetDevice(idev));
+
+    /* Verify the selected device supports mapped memory and set the device
+       flags for mapping host memory. */
+
+    checkCudaErrors(cudaGetDeviceProperties(&deviceProp, idev));
+
+#if CUDART_VERSION >= 2020
+
+    if (!deviceProp.canMapHostMemory) {
+        fprintf(stderr, "Device %d does not support mapping CPU host memory!\n", idev);
+
+        exit(EXIT_SUCCESS);
+    }
+
+    checkCudaErrors(cudaSetDeviceFlags(cudaDeviceMapHost));
+#else
+    fprintf(stderr,
+            "CUDART version %d.%d does not support "
+            "<cudaDeviceProp.canMapHostMemory> field\n",
+            ,
+            CUDART_VERSION / 1000,
+            (CUDART_VERSION % 100) / 10);
+
+    exit(EXIT_SUCCESS);
+#endif
+
+#if CUDART_VERSION < 4000
+
+    if (bPinGenericMemory) {
+        fprintf(stderr,
+                "CUDART version %d.%d does not support <cudaHostRegister> function\n",
+                CUDART_VERSION / 1000,
+                (CUDART_VERSION % 100) / 10);
+
+        exit(EXIT_SUCCESS);
+    }
+
+#endif
+
+    /* Allocate mapped CPU memory. */
+
+    nelem = 1048576;
+    bytes = nelem * sizeof(float);
+
+    if (bPinGenericMemory) {
+#if CUDART_VERSION >= 4000
+        a_UA = (float *)malloc(bytes + MEMORY_ALIGNMENT);
+        b_UA = (float *)malloc(bytes + MEMORY_ALIGNMENT);
+        c_UA = (float *)malloc(bytes + MEMORY_ALIGNMENT);
+
+        // We need to ensure memory is aligned to 4K (so we will need to padd memory
+        // accordingly)
+        a = (float *)ALIGN_UP(a_UA, MEMORY_ALIGNMENT);
+        b = (float *)ALIGN_UP(b_UA, MEMORY_ALIGNMENT);
+        c = (float *)ALIGN_UP(c_UA, MEMORY_ALIGNMENT);
+
+        checkCudaErrors(cudaHostRegister(a, bytes, cudaHostRegisterMapped));
+        checkCudaErrors(cudaHostRegister(b, bytes, cudaHostRegisterMapped));
+        checkCudaErrors(cudaHostRegister(c, bytes, cudaHostRegisterMapped));
+#endif
+    }
+    else {
+#if CUDART_VERSION >= 2020
+        flags = cudaHostAllocMapped;
+        checkCudaErrors(cudaHostAlloc((void **)&a, bytes, flags));
+        checkCudaErrors(cudaHostAlloc((void **)&b, bytes, flags));
+        checkCudaErrors(cudaHostAlloc((void **)&c, bytes, flags));
+#endif
+    }
+
+    /* Initialize the vectors. */
+
+    for (n = 0; n < nelem; n++) {
+        a[n] = rand() / (float)RAND_MAX;
+        b[n] = rand() / (float)RAND_MAX;
+    }
+
+    /* Get the device pointers for the pinned CPU memory mapped into the GPU
+       memory space. */
+
+#if CUDART_VERSION >= 2020
+    checkCudaErrors(cudaHostGetDevicePointer((void **)&d_a, (void *)a, 0));
+    checkCudaErrors(cudaHostGetDevicePointer((void **)&d_b, (void *)b, 0));
+    checkCudaErrors(cudaHostGetDevicePointer((void **)&d_c, (void *)c, 0));
+#endif
+
+    /* Call the GPU kernel using the CPU pointers residing in CPU mapped memory.
+     */
+    printf("> vectorAddGPU kernel will add vectors using mapped CPU memory...\n");
+    dim3 block(256);
+    dim3 grid((unsigned int)ceil(nelem / (float)block.x));
+    vectorAddGPU<<<grid, block>>>(d_a, d_b, d_c, nelem);
+    checkCudaErrors(cudaDeviceSynchronize());
+    getLastCudaError("vectorAddGPU() execution failed");
+
+    /* Compare the results */
+
+    printf("> Checking the results from vectorAddGPU() ...\n");
+    errorNorm = 0.f;
+    refNorm   = 0.f;
+
+    for (n = 0; n < nelem; n++) {
+        ref  = a[n] + b[n];
+        diff = c[n] - ref;
+        errorNorm += diff * diff;
+        refNorm += ref * ref;
+    }
+
+    errorNorm = (float)sqrt((double)errorNorm);
+    refNorm   = (float)sqrt((double)refNorm);
+
+    /* Memory clean up */
+
+    printf("> Releasing CPU memory...\n");
+
+    if (bPinGenericMemory) {
+#if CUDART_VERSION >= 4000
+        checkCudaErrors(cudaHostUnregister(a));
+        checkCudaErrors(cudaHostUnregister(b));
+        checkCudaErrors(cudaHostUnregister(c));
+        free(a_UA);
+        free(b_UA);
+        free(c_UA);
+#endif
+    }
+    else {
+#if CUDART_VERSION >= 2020
+        checkCudaErrors(cudaFreeHost(a));
+        checkCudaErrors(cudaFreeHost(b));
+        checkCudaErrors(cudaFreeHost(c));
+#endif
+    }
+
+    exit(errorNorm / refNorm < 1.e-6f ? EXIT_SUCCESS : EXIT_FAILURE);
+}