JetBrains Cadence

Run code directly from PyCharm in just minutes—no complex setup or cloud expertise required. Why is Cadence the right choice for ML/AI engineers? Serverless computing: Access a range of GPUs on demand and pay only for the resources consumed per second. Run code as-is: Seamlessly train your models in the cloud without making any changes. Designed for PyCharm: Maintain your existing workflow—use the terminal or debugger just like you would locally. Simplified data management: Say goodbye to manual transfers. Cadence automatically handles data synchronization, allowing you to download experiment results anytime. Reliable and reproducible: Easily review, refine, and replay experiments. Skip the queue: Schedule as many tasks as needed simultaneously. Cadence automatically checks for available hosts across different regions and zones. Why do ML/AI teams choose Cadence? Scalable GPU solutions: Instantly adjust resources through Cadence’s agile cloud platform and access a diverse range of global GPUs. Optimized GPU utilization: Cadence manages resource allocation during training to ensure GPUs are used only when needed. Transparent billing: Cadence employs a pay-as-you-go model, offering transparent spending and fine-grained control over resource consumption. Enhanced collaboration: Cadence makes it easy to share and reuse experiment results with colleagues, saving everyone time and enabling more effective teamwork.

JetBrains Cadence is a tool specifically designed for machine learning/AI engineers, enabling users to run code directly in PyCharm using powerful cloud hardware, thereby simplifying the setup of complex cloud environments and the model training process.