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KernelIDE

A browser-based IDE for practicing GPU kernel development with serverless execution on Modal.com. Write CUDA, Triton, CUTLASS, and CUTE DSL code and run it on cloud GPUs - pay only for actual execution time.

Features

  • Monaco Editor - VS Code-like editing experience with syntax highlighting and autocompletion
  • Multiple Languages - CUDA C++, Triton (Python), CUTLASS C++, CUTE DSL (Python), Mojo
  • GPU Selection - Choose from T4, L4, A10, A100, L40S, H100, H200, B200
  • Configurable Timeout - Set execution limits (5-300 seconds)
  • Serverless Execution - No idle charges, pay only for kernel runtime
  • Self-Hostable - Bring your own Modal API key
  • VSCode Extension - Use KernelIDE directly within Visual Studio Code

Quick Start

1. Install Dependencies

npm install

2. Deploy the Modal Backend

First, install the Modal CLI and authenticate:

pip install modal
modal setup  # This will open browser for authentication

after you do modal setup go to this link and create a new token by going to Create proxy auth tokens :

image

Then deploy the executor to your Modal account:

modal deploy modal_executor.py

After you run above command you'll see someting like this for the first time.

image

After deployment, you'll see your endpoint URL:

https://<your-workspace>--kernelide-executor-api.modal.run

3. Then , Run the Frontend

npm run dev

Open http://localhost:5173 in your browser, and you will see the KernelIDE like this.

image

4. Configure the IDE

  1. Click Settings in the top-right
  2. Enter your Modal API credentials
  3. Click Deploy Executoir and paste your deployed endpoint URL it should look like this https://<your-workspace>--kernelide-executor-api.modal.run to confirm the connection. after you do this, the screen should look like this in below image. image 4.Click on save settings and close the settings popup.

Usage

Web IDE

  1. Select a language from the dropdown (CUDA, Triton, CUTLASS, CUTE DSL, Mojo)
  2. Write your kernel code in the editor
  3. Choose your GPU and timeout in Settings
  4. Click Run or press Cmd/Ctrl + Enter
  5. View output and execution time in the right panel
image

VSCode Extension

The KernelIDE VSCode extension provides the same GPU kernel development experience directly in your editor.

Installation:

Download and install the pre-built extension:

# Download the extension
curl -L -o kernelide.vsix https://github.com/Tanmaypatil123/KernelIDE/releases/download/vscode-extension-v1/kernelide-0.1.0.vsix

# Install the extension
code --install-extension kernelide-0.1.0.vsix

After installation, restart VS Code and follow the setup instructions in the VSCode Extension README for complete installation and usage details.

Supported Languages

Language File Type Description
CUDA C++ .cu Native CUDA kernels with nvcc
Triton .py OpenAI Triton GPU kernels
CUTLASS C++ .cu NVIDIA CUTLASS templates
CUTE DSL .py nvidia-cutlass-dsl Python package
Mojo .mojo Modular's Mojo language

GPU Pricing (Modal.com)

GPU VRAM Approx. Price
T4 16 GB ~$0.76/hr
L4 24 GB ~$0.80/hr
A10 24 GB ~$1.10/hr
A100-40GB 40 GB ~$2.10/hr
A100-80GB 80 GB ~$2.50/hr
L40S 48 GB ~$1.70/hr
H100 80 GB ~$3.95/hr
H200 141 GB ~$4.50/hr
B200 192 GB ~$5.50/hr

Prices are approximate and per-second billing applies.

Contributing/Development

# Install dependencies
npm install

# Start dev server
npm run dev

# Build for production
npm run build

# Preview production build
npm run preview

Self-Hosting

  1. Fork/clone this repository
  2. Deploy modal_executor.py to your Modal account
  3. Build the frontend: npm run build
  4. Serve the dist/ folder with any static hosting (Vercel, Netlify, GitHub Pages, etc.)
  5. Users configure their own Modal API keys in Settings

License

MIT

Contributing

Contributions welcome! Please open an issue or PR.

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