Nvidia has announced the Jetson Orin module, the perfect solution for next generation AI and robotics applications. The module features an Nvidia Ampere architecture GPU together with deep learning and vision accelerators. Its fast memory bandwidth and high-speed IO can feed multiple concurrent AI application pipelines. This translates into being able to develop solutions using complex AI models to solve problems such as natural language understanding, 3D perception, and multi-sensor fusion.
The Jetson Orin series of system-on-modules (SOMs) deliver up to 80x the AI performance of Nvidia’s Jetson Nano. The Jetson family now boasts the Orin-based modules that span from entry-level Orin Nano to the highest performance Jetson AGX Orin. This allows customers the flexibility to easily scale applications.
Figure 1. Block diagram of Jetson Orin Nano.
The Orin Nano is the smallest Jetson form-factor, with power options from 5 to 15 W. Two versions of the Orin Nano are available, one with 4 GB of RAM and the other doubles this to have 8 GB integrated.
The Ampere Architecture GPU has up to eight streaming processors (SMs) composed of 1024 CUDA cores and up to 32 Tensor Cores used for AI processing. This delivers better performance per watt than the previous generation and allows applications to take advantage of the fine-grained structured sparsity in deep learning networks to double the throughput for Tensor Core operations.
The Jetson Orin Nano includes a six-core Arm Cortex-A78AE CPU, video decode engine, ISP, audio processing engine, and video input block. Despite its small footprint of 70 x 45 mm, the module includes various high-speed interfaces including PCIe Gen3, three 10 Gbps USB 3.2 ports, eight lanes of MIPI CSI-2 camera ports, and various sensor connections.
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