NVIDIA (NVIDIA) provides the following key technical support for artificial intelligence (AI)
NVIDIA (NVIDIA) provides the following key technical support for artificial intelligence (AI)
Graphics Processing Units (GPUs): Nvidia was originally known for its powerful Graphics Processing Units (GPUs) for gaming, design, and professional visualization. But now, their GPUs are also widely used for AI computing, especially deep learning training and inference. Nvidia's GPUs have extremely high parallel computing capabilities, making them more efficient than traditional CPUs at processing large amounts of data and computing-intensive tasks.
CUDA platform: CUDA (Compute Unified Device Architecture) is a computing platform and API developed by NVIDIA, enabling developers to use NVIDIA GPUs for general computing. CUDA has been widely used in the field of AI and deep learning, allowing researchers and developers to use NVIDIA hardware more efficiently.
AI software and development tools: Nvidia has developed a series of AI software and development tools, including TensorRT, cuDNN, DALI, etc., to support the development of AI and deep learning. In addition, NVIDIA also provides some pre-trained deep learning models and AI application development frameworks, such as DeepStream and Transfer Learning Toolkit.
AI hardware platforms: In addition to GPUs, Nvidia has also developed some hardware platforms specifically for AI applications, such as the Jetson series (for embedded AI applications) and the DGX series (for AI research and large-scale industrial applications).
Application of AI in the data center: Nvidia's data center GPU and network technology can help build a powerful AI computing infrastructure and support the large-scale deployment and operation of AI in the cloud.
Autonomous driving technology: Nvidia's Drive platform is an AI solution for self-driving cars and trucks, which can perform various autonomous driving tasks such as environment perception, map construction, and path planning.
The following five chips that mainly apply autonomous driving technology are briefly described. Some of them are widely used in automotive and autonomous driving technology:
1: TDA2x series: This is a System-on-Chip (SoC) for Advanced Driver Assistance Systems (ADAS) with vision processing for environment awareness and multi-camera applications. Such as TDA2003AH, TDA2003AH, TDA20137, TDA20137/1,557, TDA2030V, etc.
2: TDA3x series: This is a more compact ADAS SoC for forward-facing camera and driver monitoring systems, including low-power applications. For example TDA3602/N3,112, TDA3606AT/N1,112, TDA3608TH/N3C,512, TDA3616SF/N1,112 etc.
3:DRA77x "Jacinto 6 EP" series: These are SoCs designed for automotive infotainment and service systems, supporting multiple processor cores and multiple graphics engines.
4: AWR1x series: This is a family of millimeter-wave radar sensors for automotive radar applications, including environmental awareness and autonomous driving.
5: DRA829V Jacinto 7 processor: used for automotive gateways, electric vehicle (EV) charging piles and industry 4.0 applications. For example DRA829VMTGBALFR produced by Texas Instruments (TI)
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