Discover why AI and accelerated computing are essential to every CTO in telecommunications.
The world of ubiquitous connectivity in which we now live, and the tidal wave of consumptive devices serving infinite streams of data are unrelenting. The telecommunications industry has played a significant role in the evolution of apps everywhere—irreversibly altering both developer and consumer behaviors and expectations.
We find ourselves surging into a world that will not only be connected, but demand substantial computing resources for each connected device. Cars, refrigerators, and even washing machines will function as connected devices, generating petabytes of data. The amount of data each device produces will be 300X-500X more than today’s smartphone. If every car on the road today became a connected computing device, networks would have over one billion additional devices to serve, requiring colossal amounts of cloud computation.
The demand on the wireless industry to absorb, process, and deliver data is rising at an unprecedented scale. It’s time for telecommunications to not only tap into the technologies that enable incremental progress—but those that are defining the future.
As GPUs continue to equip the future of computing, here are three things every visionary CTO should consider:
GPUs Offer a Quantum Leap in Network Efficiency
The future of Telco ultimately comes down to the cost efficiency of the network infrastructure and flexibility of its hardware. Therefore Telcos are moving to 5G software-defined networks (SDN), and virtualized network functions (VNFs). GPUs could increase the price-performance of VNFs by 20x while unleashing the power of cloud native architecture.
Moving to VNFs is no easy feat. Telcos may find their performance actually degrades as they move to general purpose computing platforms like CPUs. Many of these functions were not designed for cloud-native environments, and CPUs are not inherently good at processing very complex and high-demand network functions. GPUs are incredibly efficient at processing parallelizable code and offer a paradigm shift around the capabilities and possibilities for VNFs. Telcos need to rethink the software and computing architecture for their future VNFs and SDNs.
Networks Optimized with AI Reduce Costs and Increase Productivity
The primary motivation for the adoption of AI and ML in network operations is gaining the ability to manage their exponentially increasing complexity, and the realtime optimization required in SDNs. Another key driver of adoption is the pervasive requirement to minimize labor-intensive operational expenses and increase end-user productivity.
It’s becoming increasingly unreasonable to expect that professionals can handle the increasing scope, complexity, and scale of networks. Even the best operation professionals can’t contemplate the number of simultaneous variables present in today’s networks, especially in SDN/VNF environments. Therefore, embracing AI/ML in network operations is essential to future success.
Many network operations are based on statistical algorithms, static rules, and policies, and the network can be optimized by converting these policies and rules into deep learning functions. Verizon for example, was using a traditional mission learning algorithm called ARIMA for forecasting network traffic. With NVIDIA they were able to convert that to a deep learning algorithm and have gone from 24 hours of compute time to one hour. It’s all about optimizing the performance of the data center with deep learning—and this is just one example of what can be done.
GPUs Enable New Telco Services at the EDGE
GPU-accelerated networks will make it possible for Telcos to deliver ultra-high definition 360-degree immersive experiences to their customers anywhere. Drones and robots with connected computing are beginning to learn from one another and behave communally. Autonomous vehicles will also use GPU-accelerated networks to expand their perception—and in turn source its network with data.
These insights are just a glimpse of the future GPU powered networks will enable. As telco companies continue to drive innovation, deploying AI will be essential to meeting the network demands of tomorrow and remaining on the cutting edge.
- Join us at the GPU Technology Conference (GTC). Connect with technology experts from NVIDIA and other leading organizations. Gain insights and valuable hands-on training through hundreds of sessions. Discover how GPU technologies are creating amazing breakthroughs in important fields such as deep learning. Hear about disruptive innovations that can transform your work.
- Explore the NVIDIA Deep Learning Institute, which offers Developer certification in AI and accelerated computing through online courses, online electives, and instructor-led workshops.
- Start innovating with the NVIDIA GPU Cloud (NGC). Access a comprehensive catalog of GPU-accelerated containers for deep learning software, HPC applications, and HPC visualization. Get up and running quickly and reduce the complexity typically associated with setting up software.