TensorRT

TECHNICAL DEFINITION

TensorRT is an NVIDIA SDK for high-performance deep learning inference, comprising a deep learning optimizer and runtime that delivers low-latency and high-throughput inference for trained neural networks on NVIDIA GPUs by applying graph optimizations, layer fusions, and precision calibration.

BACKGROUND

A large language model (LLM) is a neural network trained on a vast amount of text for natural language processing tasks, especially language generation. LLMs can typically generate, summarize, translate, and analyze text in many contexts, and are a foundational technology behind modern chatbots. Biased or inaccurate training data can make an LLM's output less reliable.

SYNONYMS & ALIASES

• NVIDIA TensorRT
• GPU inference optimizer
• Deep learning inference engine

USAGE NOTE

TensorRT is widely used in production environments to accelerate the inference speed of large AI models on NVIDIA hardware.

DEVELOPERS

Organizations developing technology related to TensorRT.

• NVIDIA

  NVIDIA is the creator and primary developer of TensorRT, an SDK for high-performance deep learning inference, and continues to evolve its features and integrations.

• Microsoft

  Microsoft integrates TensorRT into its Azure Machine Learning platform and ONNX Runtime to accelerate deep learning inference on NVIDIA GPUs, offering optimized deployments.

• Meta (Facebook AI)

  Meta's PyTorch framework integrates with TensorRT through Torch-TensorRT, allowing developers to leverage TensorRT's optimizations directly within their PyTorch models for deployment.

• Google

  Google Cloud offers GPU-accelerated computing instances and tools that support TensorRT for optimizing deep learning inference in environments like Google Kubernetes Engine and AI Platform.

• Amazon Web Services (AWS)

  AWS provides services like Amazon SageMaker and Deep Learning AMIs that support and often pre-install TensorRT, enabling users to deploy high-performance deep learning models on NVIDIA GPUs.

• Baidu

  Baidu's PaddlePaddle deep learning framework features strong support for NVIDIA hardware and integrates TensorRT for efficient model deployment and accelerated inference.

• OpenAI

  As a leading AI research organization, OpenAI utilizes and contributes to technologies like TensorRT to achieve highly optimized and scalable inference for their large language models and other AI systems.

• Dell Technologies

  Dell provides high-performance computing and AI infrastructure solutions, including servers equipped with NVIDIA GPUs, often with software stacks pre-optimized to leverage TensorRT for AI workloads.

• IBM

  IBM offers AI hardware and software solutions, including its PowerAI platform and cloud services, that utilize NVIDIA GPUs and integrate with TensorRT for accelerated deep learning inference.