cuda-samples/cpp/0_Introduction/simplePrintf/README.md

Sample: Device-Side printf (simplePrintf)

Description

A first-look CUDA sample: call C's printf from inside a CUDA kernel. Every thread in a 2D grid of 3D blocks prints its own block and thread identifiers along with a shared value passed from the host. The CUDA runtime buffers the device-side output and flushes it to the host's standard output when the kernel completes.

This sample is the canonical demonstration of device-side printf, the simplest debugging and tracing tool available inside kernel code. It also shows how multidimensional blockIdx/threadIdx coordinates are flattened into linear indices.

What You'll Learn

• Calling printf directly from device code (__global__ kernel)
• Launching a kernel with a 2D grid (dim3 dimGrid(2, 2)) of 3D blocks (dim3 dimBlock(2, 2, 2))
• Flattening multidimensional block and thread indices into a single linear index
• Flushing device-side printf output to the host with cudaDeviceSynchronize
• Querying the active device with cudaGetDevice / cudaGetDeviceProperties

Key Concepts

• Device-side printf — formatted output from within a kernel; output is buffered per launch and flushed at a synchronization point
• Multidimensional launch geometry — gridDim, blockIdx, blockDim, and threadIdx are dim3 values with .x, .y, .z components
• Index linearization — converting (x, y, z) coordinates into a flat index:
  • block: blockIdx.y * gridDim.x + blockIdx.x
  • thread: threadIdx.z * blockDim.x * blockDim.y + threadIdx.y * blockDim.x + threadIdx.x

Key APIs

CUDA Runtime

• cudaSetDevice — select the active GPU
• cudaDeviceGetAttribute — query compute capability (major, minor) and SM count
• cudaDeviceSynchronize — block the host until the kernel finishes, which also flushes the device printf buffer

Device

• printf — standard C formatted output, callable from __global__/__device__ code (requires Compute Capability 2.0 or higher)

Requirements

Hardware

• NVIDIA GPU with Compute Capability 2.0 or higher (device-side printf is unavailable on earlier architectures)

Software

• CMake 3.20 or newer
• A C++17-capable host compiler

How to Build

See the top-level README for full build instructions, including how to build all samples or a single sample standalone.

How to Run

./simplePrintf

Expected Output

The launch uses a 2×2 grid of 2×2×2 blocks = 4 blocks × 8 threads = 32 lines. Each thread prints its linear block index, its linear thread index, and the value 10. Because blocks and threads run concurrently, the order of the lines will vary between runs:

GPU Device 0: with compute capability X.Y and Number of SMs <smCount>
printf() is called. Output:

[0, 0]:		Value is:10
[0, 1]:		Value is:10
[0, 2]:		Value is:10
...
[3, 7]:		Value is:10

Files

• simplePrintf.cu — device-side printf kernel + host driver
• README.md — this file
• CMakeLists.txt — build configuration

See Also

• CUDA C++ Programming Guide — printf()