Xilinx : Strategy to move Data Acceleration Closer to that Data

With the continuing advance of cloud computing, artificial intelligence, the Internet of Things and other drivers of computing demand, enterprises managing huge exabyte-scale data centers need to move more and more data faster and faster. One secret to handling that traffic growth is to bring new data acceleration capabilities closer to the data itself.

That's the concept advanced by Manish Muthal, the Vice President of Data Center Marketing here at Xilinx, in a keynote address he delivered Aug. 8 at the 2018 Flash Memory Summitheld at the Santa Clara Convention Center in Silicon Valley.

A new class of data acceleration platforms is needed to enable tomorrow's exabyte-scale data centers, Manish said in his address. He identified a number of 'brick walls' that he said have stymied the performance of data delivery across networks over the years as the amount of data, the number of applications and the demand for faster speeds has grown exponentially.

Among the brick walls has been a limit on the number of individual transistors that a data center could support, the limitations of single-thread processor performance, limits on radio frequencies, the growing electrical power demands on a network and limitations on the amount of cores that could be supported per machine.

As each of these brick walls arose, Manish said Xilinx overcame them by developing heterogeneous computing architectures that delivered data acceleration, such as its FPGAs, MPSoCs and its new Adaptive Compute Acceleration Platform (ACAP).

'We now need to move to a paradigm of heterogeneous computing architectures,' he said in his keynote. 'These accelerators are going to play a key role to help us scale performance in a cost- and power-efficient manner.'

Moving compute acceleration closer to data is key to the success of emerging and next generation cloud data centers, he said. These accelerators will need to be easy to deploy and manage and must be highly adaptable to the ever-changing workloads within cloud environments.

Initially, heterogeneous computing was used to enable machine learning and training or traditional applications such as database management or video, Manish explained. But as demand for more compute capability grows, data centers need to offer 'adaptable acceleration.' Besides database and video, adaptable acceleration is also needed to do big data analytics, financial risk modeling and genomics, as well as storage networking and security.

Xilinx took the opportunity at this year's Flash Memory Summit to exhibit its next-generation flash storage solutions across ecosystems, partners, and customers.

View Manish's full keynote

If you are interested in learning more about storage acceleration or any other type of Xilinx-powered technology, we encourage you to join us at the Xilinx Developer Forumcoming up on Oct. 1 and 2, 2018, at the San Jose Fairmont in downtown San Jose. Hope to see you there!