BARCELONA, Spain, February 26, 2024 — As part of the Innovative Optical and Wireless Network (IOWN) initiative, NTT Company (NTT) and Red Hat, Inc.in collaboration with NVIDIA and Fujitsu, have jointly developed a solution to enhance and expand the potential of real-time artificial intelligence (AI) data analysis at the edge.
Utilizing technologies developed by the IOWN Global Forum and built on top of Red Hat OpenShift, the industry’s leading hybrid cloud application platform powered by Kubernetes, this solution received proof of concept (PoC) recognition from the IOWN Global Forum for its real-world viability and use cases.
As innovation in AI, sensing technology and networking continues to accelerate, using AI analytics to evaluate and sort inputs at the network edge will be critical, d ‘especially since data sources are developing almost daily. However, using AI analytics at scale can be slow and complex, and may be associated with higher maintenance costs and software maintenance to integrate new AI models and additional hardware . With edge computing capabilities emerging in more remote locations, AI analytics can be placed closer to sensors, reducing latency and increasing bandwidth.
“NTT Group, in close collaboration with its partners, is accelerating the development of IOWN to achieve a sustainable society,” said Katsuhiko Kawazoe, Senior Executive Vice President of NTT and Chairman of the IOWN Global Forum. “This IOWN PoC is an important step towards green computing for AI, which supports the collective intelligence of AI. We are further improving IOWN’s energy efficiency by applying photonic-electronic convergence technologies to an IT infrastructure. We aim to embody the sustainable future of net zero emissions with IOWN.
This solution includes the IOWN All-Photonics Network (APN) and data pipeline acceleration technologies in IOWN’s Data Centric Infrastructure (DCI). NTT’s accelerated data pipeline for AI adopts Remote Direct Memory Access (RDMA) over APN to efficiently collect and process large amounts of edge sensor data. Red Hat OpenShift container orchestration technology provides greater flexibility to manage workloads within the accelerated data pipeline in geographically distributed and remote data centers. NTT and Red Hat have successfully demonstrated that this solution can effectively reduce power consumption while maintaining lower latency for real-time AI analytics at the edge.
The proof of concept evaluated a real-time AI analytics platform with Yokosuka City as the sensor installation base and Musashino City as the remote data center, both connected via APN. As a result, even when a large number of cameras were installed, the latency required to aggregate sensor data for AI analysis was reduced by 60% compared to conventional AI inference workloads . Additionally, IOWN PoC testing demonstrated that the power consumption required for AI analysis for each edge camera could be reduced by 40% compared to conventional technology. This real-time AI analysis platform allows the GPU to be scaled to accommodate a larger number of cameras without the CPU becoming a bottleneck. According to a trial calculation, assuming that 1,000 cameras can be installed, energy consumption should be reduced by a further 60%. The highlights of the proof of concept of this solution are as follows:
- Accelerated data pipeline for AI inference, provided by NTT, uses RDMA over APN to directly fetch large-scale sensor data from local sites to the memory of an accelerator in a remote data center, thereby reducing protocol management overhead in the conventional network. It then completes the processing of AI inference data within the accelerator with less CPU control overhead, thereby improving the energy efficiency of AI inference.
- Real-time, large-scale AI data analysispowered by Red Hat OpenShift, can help Kubernetes operators minimize the complexity of implementing hardware accelerators (GPU, DPU, etc.), enabling improved flexibility and easier deployment across disaggregated sites, including remote data centers.
- This PoC uses NVIDIA A100 Tensor Core GPUs and NVIDIA ConnectX-6 network cards for AI inference.
This solution helps pave the way for intelligent AI-driven technologies that will help businesses scale sustainably. With this solution, organizations can benefit from:
- Reduced overhead costs associated with collecting large amounts of data.
- Enhanced data collection that can be shared between metro areas and remote data centers for faster AI analysis.
- The ability to use locally available and potentially renewable energy, such as solar or wind power.
- Increased security of area management through video cameras acting as sensors.
Learn more about this solution at IOWN Global Forum Session at MWC Barcelona scheduled for February 29, 2024.
About Red Hat
Red Hat is the world’s leading provider of enterprise open source software solutions, using a community-driven approach to deliver reliable, high-performance Linux, hybrid cloud, container and Kubernetes technologies. Red Hat helps customers integrate new and existing IT applications, develop cloud-native applications, standardize on their industry-leading operating system, and automate, secure, and manage complex environments. Award-winning support, training and consulting services make Red Hat a trusted Fortune 500 advisor. As a strategic partner to cloud providers, system integrators, application providers, customers and communities open source, Red Hat can help organizations prepare for changing circumstances. digital future.
About NTT
NTT contributes to a sustainable society through the power of innovation. We are a leading global technology company providing services to consumers and businesses as a mobile operator, infrastructure, network, applications and consulting provider. Our offerings include digital business consulting, managed application services, workplace and cloud solutions, data centers and edge computing, all supported by our deep global industry expertise. We generate more than $97 billion in revenue and 330,000 employees, with $3.6 billion in annual R&D investments. Our operations span more than 80 countries and regions, enabling us to serve customers in more than 190 of them.
Source: Red Hat
