The proliferation of smart mobile devices, video, user-generated content and social networking, and the rising adoption of cloud services for both enterprise and consumer services are all driving explosive growth of wireless networking infrastructure. Globally, mobile data traffic is expected to grow 18-fold between 2011 and 2016, reaching 10.8 exabytes per month by 2016. Today, video traffic alone accounts for 40 percent of the wireless network load. The number of mobile devices connected to wireless networks will reach 25 billion, averaging 3.5 devices for every person on the planet, by 2015. That number is expected to double, to 50 billion, by 2020.This growth in storage capacity and network traffic is far outstripping the infrastructure build-out required to support it, a phenomenon known as the data deluge gap.
To bridge this gap, the industry needs to leverage smarter silicon technology to scale datacenter infrastructures more cost effectively. Besides helping close the data deluge gap, smarter data processing offers potential dramatic improvements in application performance. A recent survey of 412 European datacenter managers conducted by LSI revealed that while 93 percent acknowledged the critical importance of improving application performance, a full 75% do not feel that they are achieving the desired results. This indicates that there is rising pressure on datacenter managers to find smarter ways to push systems to do much more work within the same power and cost profiles.
Smart software running on general-purpose processors, increasingly with multiple cores, is pervasive in the datacenter. Processors have long inhabited switches and routers, firewalls and load-balancers, WAN accelerators and VPN gateways. None of these systems are fast enough, however, to keep pace with the data deluge on its own, for a basic reason: general-purpose processors must treat every byte equally. While such equality is perfectly acceptable for system-level versatility, it is inadequate for low-level, high-volume packet processing.
This reality is driving the need for more intelligence in silicon that is purpose-built for specific networking applications to provide the right balance of performance, power consumption and programmability. Today’s smart silicon has reached a level of price/performance that makes it more cost-effective than adding general-purpose processors.
The latest generation of smart silicon typically features multiple cores of general-purpose processors and multiple acceleration engines for common networking functions, such as packet classification with deep packet inspection, security processing, especially for encryption and decryption, and traffic management.
Some of these acceleration engines are so powerful they can completely offload specialized network processing from general-purpose processors, making it easier to perform switching, routing and other networking functions entirely in smart line cards installed in servers and networking appliances to further accelerate overall network performance.
In many organizations today, microseconds matter, driving strong demand for faster response times. For trading firms, latency can be measured in millions of dollars per millisecond. For others, such as online retailers, every millisecond of delay can mean lost sales and fading customer loyalty. Tomorrow’s datacenter networks will need to be both faster and flatter, and therefore, smarter than ever. To eliminate the data deluge gap and maximize performance, systems need to be smarter, and those smarts will increasingly need to take the form of purpose-built silicon.
About the Author
Michael Merluzzi is product marketing manager in the Networking Solutions Group of LSI Corporation. Focusing on mobile backhaul applications, Merluzzi is responsible for marketing of integrated platform solutions and application-enabling software for the LSI Axxia family of multicore communication processors. Previously, he held a variety of roles in technical marketing, applications engineering and software development. Merluzzi holds a bachelor's degree in Electrical Engineering from The Pennsylvania State University and master's degrees in Business Administration and Computer Engineering from Lehigh University.