NVIDIA has this week announced the availability of production models of the NVIDIA Jetson AGX Orin 32GB with the Jetson AGX Orin developer kit, capable of providing developers with up to up to 275 trillion operations per second, supports multiple concurrent AI application pipelines with an NVIDIA Ampere architecture GPU, next-generation deep learning and vision accelerators, high-speed I/O, and fast memory bandwidth.
NVIDIA Jetson
The new NVIDIA Jetson AGX Orin 32 GB production module is available in the Jetson store from retail and distribution partners worldwide.
“The four Jetson Orin-based production modules, announced at GTC, offer customers a full range of server-class AI performance. The Jetson AGX Orin 32 GB module is available to purchase now, while the 64 GB version will be available in November. Two Orin NX production modules are coming later this year. The production systems are supported by the NVIDIA Jetson software stack, which has enabled thousands of enterprises and millions of developers to build and deploy fully accelerated AI solutions on Jetson.”
Jetson AGX Orin 32GB Module
– AI Perf: 200 TOPS (INT8)
– GPU: NVIDIA Ampere architecture with 1792 NVIDIA CUDA cores and 56 Tensor Cores
– CPU: 8-core Arm Cortex-A78AE v8.2 64-bit CPU 2MB L2 + 4MB L3
– Memory: 32GB 256-bit LPDDR5 204.8 GB/s
– Storage: 64GB eMMC 5.1
Jetson AGX Orin Developer Kit
– AI Perf: 275 TOPS
– GPU: NVIDIA Ampere architecture with 2048 NVIDIA CUDA cores and 64 tensor cores
– CPU: 12-core Arm Cortex-A78AE v8.2 64-bit CPU 3MB L2 + 6MB L3
– Memory: 32GB 256-bit LPDDR5 | 204.8 GB/s
– Storage: 64GB eMMC 5.1
“On top of JetPack SDK, which includes the NVIDIA CUDA-X accelerated stack, Jetson Orin supports multiple NVIDIA platforms and frameworks such as Isaac for robotics, DeepStream for computer vision, Riva for natural language understanding, TAO Toolkit to accelerate model development with pretrained models, and Metropolis, an application framework, set of developer tools and partner ecosystem that brings visual data and AI together to improve operational efficiency and safety across industries.”
Source : NVIDIA
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