printf Inside a Kernel
Seeing output from device threads.
printf Inside a Kernel is a free CUDA Academy lesson on CoddyKit — lesson 3 of 4. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the CUDA Academy learning path, one of 4 lessons in the course, and your progress syncs across the web and the CoddyKit app.
Printing from the GPU
Believe it or not, you can call printf right inside a kernel. It is the simplest way to peek at what your threads are doing. 👀
__global__ void hi() {
printf("Hello from the GPU\n");
}Every Thread Prints
Remember the kernel runs in every thread, so a single printf line fires once per thread. Launch 256 threads and you get 256 lines.
hi<<<1, 256>>>(); // 256 hellosIdentify Each Thread
Include the threadIdx in your message so you can tell threads apart. Otherwise the output is just a wall of identical lines.
printf("thread %d\n", threadIdx.x);Output Order Is Not Fixed
Threads run in parallel, so the printed order is unpredictable. Do not rely on lines arriving in index sequence.
Format Strings Work
Device printf supports the usual format specifiers like %d, %f, and %s. It feels just like host printf.
printf("i=%d val=%f\n", i, x[i]);Output Goes to a Buffer
Device output is staged in a GPU buffer and flushed to your console later, not the instant printf runs. That is normal.
You Must Wait to See It
Because the launch is async, you will not see prints until the GPU finishes. Call cudaDeviceSynchronize to flush them.
hi<<<1, 4>>>();
cudaDeviceSynchronize();Guard Heavy Printing
Printing from millions of threads floods the buffer. Guard it so only thread 0 prints, or only a few do.
if (threadIdx.x == 0) printf("block done\n");Great for Quick Debugging
printf is your fastest debugging tool: drop one in to check an index or a value, confirm the bug, then remove it.
printf("i=%d should be < n=%d\n", i, n);It Slows Kernels Down
Heavy printing hurts performance badly. Use it to find a problem, then delete it before you measure real speed.
Old GPUs May Differ
Device printf needs a reasonably modern compute capability (2.0 and up). Almost every current GPU supports it just fine.
Quick Check
Check what you know about device printf.
Recap: Kernel printf
Use printf to peek inside threads, add threadIdx to tell them apart, sync to flush, and remove it before timing. Handy tool! 🎉
Frequently asked questions
Is the “printf Inside a Kernel” lesson free?
Yes — the full text of “printf Inside a Kernel” is free to read here on the web, and the CUDA Academy course includes 4 lessons in total. To practise it interactively (a built-in code editor and a 24/7 AI tutor) and unlock the rest of the CUDA Academy course, upgrade to CoddyKit PRO.
What will I learn in “printf Inside a Kernel”?
Seeing output from device threads. You practise CUDA Academy with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.
Do I need any experience to start CUDA Academy?
No prior experience is required. CUDA Academy on CoddyKit is structured for beginners through advanced learners; this is — lesson 3 of 4, so you can start here or from the beginning and move at your own pace.
How long does the “printf Inside a Kernel” lesson take?
Most CoddyKit lessons take about 5–10 minutes. Each one is bite-sized and interactive, so you make steady progress and pick up exactly where you left off across the web and the app.
Can I write and run code in this CUDA Academy lesson?
Yes. Every CUDA Academy lesson includes a built-in code editor, so you write and run real code right in your browser and get instant AI feedback — no local setup required.
All lessons in this course
- Anatomy of a Kernel
- The Triple-Angle-Bracket Launch
- printf Inside a Kernel
- cudaDeviceSynchronize Explained