Enterprises struggle to support edge workloads

The use of edge computing is driving a need for more local computing power, but a new study reveals that enterprises are facing problems when it comes to supporting edge workloads.

The survey of more than 300 storage professionals from computational storage specialist NGD systems finds that while enterprises are rapidly deploying technologies for real-time analytics, machine learning and IoT, they are still using legacy storage solutions that are not designed for such data-intensive workloads.

In fact, 54 percent of respondents say their processing of edge applications is a bottleneck, and they want faster and more intelligent storage solutions. 60 percent say they are using Non-volatile memory Express (NVMe) SSDs to speed up handling of large data sets but that this hasn’t solved their problem.

Of respondents 86 percent expect storage's future to rely on NVMe SSDs, while 63 percent say NVMe SSDs have helped with superior storage speed. However, 67 percent report budget and cost as issues preventing the use of NVMe SSDs.

"We were not surprised to find that while more than half of respondents are actively using edge computing, more than 70 percent are using legacy GPUs, which will not reduce the network bandwidth, power and footprint necessary to analyze mass data-sets in real time," says Nader Salessi, CEO and founder of NGD Systems. "Computational Storage provides an innovative solution to today’s architecture, in which compute moves closer to where data is generated, rather than the data being moved up to compute. This is why computational storage is ideal for any organization deploying edge computing as its new model; it makes it possible to process data right where it's created and needed, speeding up the time to analyze petabytes of data."

Among other findings are that 46 percent of respondents say they do not have the infrastructure in place to do proper computing at the data-generation site. 70 percent of respondents say they are using GPUs to help improve workload performance, while 73 percent want lower power consumption and 81 percent want a smaller footprint.

The full report is available from the NGD website.

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