NVIDIA TensorRT Inference Server 0.9.0 Beta

The NVIDIA TensorRT Inference Server (TRTIS) provides a cloud inferencing solution optimized for NVIDIA GPUs. The server provides an inference service via an HTTP or GRPC endpoint, allowing remote clients to request inferencing for any model being managed by the server.

What's New in 0.9.0 Beta

• TRTIS now monitors the model repository for any change and dynamically reloads the model when necessary, without requiring a server restart. It is now possible to add and remove model versions, add/remove entire models, modify the model configuration, and modify the model labels while the server is running.
• Added a model priority parameter to the model configuration. Currently the model priority controls the CPU thread priority when executing the model and for TensorRT models also controls the CUDA stream priority.
• Fixed a bug in GRPC API: changed the model version parameter from string to int. This is a non-backwards compatible change.
• Added --strict-model-config=false option to allow some model configuration properties to be derived automatically. For some model types, this removes the need to specify the config.pbtxt file.
• Improved performance from an asynchronous GRPC frontend.