NVIDIA和Arm合作将深度学习应用于数十亿物联网设备
NVIDIA Deep Learning Accelerator IP to be Integrated into Arm Project Trillium Platform, Easing Building of Deep Learning IoT Chips
SAN JOSE, Calif.—GPU Technology Conference—March 27, 2018—NVIDIA and Arm today announced that they are partnering to bring deep learning inferencing to the billions of mobile, consumer electronics and Internet of Things devices that will enter the global marketplace.
Under this partnership, NVIDIA and Arm will integrate the open-source NVIDIA Deep Learning Accelerator (NVDLA) architecture into Arm’s Project Trillium platform for machine learning. The collaboration will make it simple for IoT chip companies to integrate AI into their designs and help put intelligent, affordable products into the hands of billions of consumers worldwide.
“Inferencing will become a core capability of every IoT device in the future,” said Deepu Talla, vice president and general manager of Autonomous Machines at NVIDIA. “Our partnership with Arm will help drive this wave of adoption by making it easy for hundreds of chip companies to incorporate deep learning technology.”
“Accelerating AI at the edge is critical in enabling Arm’s vision of connecting a trillion IoT devices,” said Rene Haas, executive vice president, and president of the IP Group, at Arm. “Today we are one step closer to that vision by incorporating NVDLA into the Arm Project Trillium platform, as our entire ecosystem will immediately benefit from the expertise and capabilities our two companies bring in AI and IoT.”
Based on NVIDIA® Xavier™, the world’s most powerful autonomous machine system on a chip, NVDLA is a free, open architecture to promote a standard way to design deep learning inference accelerators. NVDLA’s modular architecture is scalable, highly configurable and designed to simplify integration and portability.
NVDLA brings a host of benefits that speed the adoption of deep learning inference. It is supported by NVIDIA’s suite of powerful developer tools, including upcoming versions of TensorRT, a programmable deep learning accelerator. The open-source design allows for cutting-edge features to be added regularly, including contributions from the research community.
The integration of NVDLA with Project Trillium will give deep learning developers the highest levels of performance as they leverage Arm’s flexibility and scalability across the wide range of IoT devices.
“This is a win/win for IoT, mobile and embedded chip companies looking to design accelerated AI inferencing solutions,” said Karl Freund, lead analyst for deep learning at Moor Insights & Strategy. “NVIDIA is the clear leader in ML training and Arm is the leader in IoT end points, so it makes a lot of sense for them to partner on IP.”
About Arm
Arm technology is at the heart of a computing and connectivity revolution that is transforming the way people live and businesses operate. Our advanced, energy-efficient processor designs are enabling the intelligence in more than 125 billion silicon chips and securely powering products from the sensor to the smartphone to the supercomputer. With more than 1,000 technology partners, including the world’s largest consumer brands, we are driving Arm innovation into all areas compute is happening inside the chip, the network and the cloud.
About NVIDIA
NVIDIA’s (NASDAQ: NVDA) invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots and self-driving cars that can perceive and understand the world. More information at http://nvidianews.nvidia.com/.
Related Semiconductor IP
- High performance GPU for cloud gaming with DirectX support
- GPU based on Arm's 5th Gen architecture
- High Performance GPU for premium DTVs
- Efficient GPU ideal for integrating into smart home hubs, set-top boxes or mainstream DTVs
- Smallest GPU to support native HDR applications, suitable for wearable devices, smart home hubs, or mainstream set-top boxes
Related News
- SiFive宣布推出首款采用NVIDIA深度学习加速器技术的开源RISC-V SoC平台
- Altek授权CEVA图像和视觉DSP用于移动设备中的深度学习
- 哈佛研究人员选择Flex Logix的嵌入式FPGA技术来设计深度学习SoC
- Synopsys和Morpho协作加速深度学习算法在嵌入式视觉上的应用