GPU Playground — Run CUDA C++, PyTorch & CuPy Online on Real GPUs
Press "Run" to execute on a real GPU.
Frequently Asked Questions About the GPU Playground
What languages does the playground support?
The playground supports CUDA C++ and Python (including PyTorch and CuPy). Switch between CUDA C++ and Python using the language selector in the toolbar. All code runs on real NVIDIA T4 GPUs in the cloud.
Can I run PyTorch code online?
Yes. Switch to Python mode and import torch. PyTorch is pre-installed on the GPU server. You can run tensor operations, check CUDA availability, benchmark matrix multiplies, and prototype neural network layers — all on a real NVIDIA GPU without any local setup.
Can I run CuPy code online?
Yes. CuPy is a NumPy-compatible GPU array library. Switch to Python mode and import cupy to accelerate NumPy-style operations on the GPU. Great for scientific computing without writing CUDA kernels manually.
What is CUDA?
CUDA (Compute Unified Device Architecture) is a parallel computing platform and programming model developed by NVIDIA. It allows developers to use NVIDIA GPUs for general-purpose computing, dramatically accelerating applications like machine learning, scientific simulations, image processing, and more.
Do I need a GPU to use the playground?
No. The playground runs your code on cloud-hosted NVIDIA T4 GPUs. You only need a web browser and an internet connection.
Is the playground free?
Yes. You get 30 free credits every month. Each code execution costs 1 credit. Upgrade to Starter (300 credits/mo) or Pro (700 credits/mo) for more.
What GPU does the playground use?
The playground runs on NVIDIA T4 GPUs with full CUDA 12 support, nvcc compiler, and PyTorch pre-installed. Python mode also supports CuPy and other GPU-accelerated libraries.
Can I learn CUDA programming with this tool?
Absolutely. The playground is designed for learning GPU programming. Experiment with CUDA kernels, understand thread indexing, practice memory management, and prototype PyTorch extensions — all without local setup.
What CUDA features are supported?
Full CUDA C/C++ support including kernel declarations, thread hierarchy, shared memory, constant memory, CUDA streams, events, and the complete CUDA runtime API.
How is this different from other online compilers?
Unlike generic online compilers, this playground supports CUDA C++ and Python (PyTorch, CuPy) with real GPU execution on NVIDIA hardware. It is purpose-built for GPU programming and machine learning.
Do I need to install anything?
No. All compilation and execution is handled server-side. Just write your code and click Run.
Who is the playground for?
Students learning GPU programming, researchers prototyping PyTorch models, developers writing CUDA kernels, and anyone who needs quick access to a real NVIDIA GPU without the setup overhead.