Forest Runtime is a robust execution platform for neural network models, providing a retargetable and modular architecture suited for various hardware environments, from data centers to mobile and TinyML applications. It facilitates the seamless execution of compiled models using common C++ APIs along with C and Python bindings, making it versatile for a broad range of AI applications. The runtime supports 'hot batching' technology, allowing models to alter batch sizes and input shapes at runtime, which is essential for modern neural networks like BERT and DLRM. This feature maximizes hardware utilization and minimizes response time by dynamically connecting various system resources efficiently. It also incorporates unique 'bridging' technology that allows resource-sharing among multiple accelerator cards and sessions, thereby supporting scalability and high throughput in server environments.
