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Improve infrastructure performance with these compute and data tips
This article is part of the Storage issue of October 2018, Vol. 17, No. 7
It's all about time. Time is a non-renewable resource that only moves forward. Once spent, it can't be reclaimed or rewound. Time is the construct that separates events and moments. With IT operations, there's never enough of it. No one ever said they needed less time. There's unceasing pressure to do more with every second. Take the example of high-performance computing (HPC), aka supercomputers, and the ever-constant pursuit to increase the number of calculations or floating-point operations per second (FLOPS) they perform. Measured today in the dozens to hundreds of petaFLOPS, the next goal is exaFLOPS, a thousand times faster. That same unrelenting burden is readily apparent in storage. Storage infrastructure performance is measured in IOPS and throughput per second -- megabytes to gigabytes per second moving to terabytes per second. It's this perpetual hunger for greater infrastructure performance per second that's the unspoken premise behind the question: Does it make more sense to move the data or the compute? No ...
Features in this issue
Perpetual hunger for better and faster application performance often requires reducing latency by either moving the data to the compute or the compute to the data, but which one?
Data, software and hardware migration projects should, but don't always, fully exploit the features and settings of the new environment and minimize application downtime.
Cost and scaling limits mean planar NAND flash as we know it will slowly cede its pre-eminent place in the memory hierarchy to emerging technologies such as 3D XPoint.
News in this issue
Forget everything you've heard about private cloud storage and start over with a true set of building blocks designed to let you create a public cloud-like infrastructure.
Columns in this issue
StorOne's TRU Storage technology raises the bar for software-defined storage by gathering together universal pools of storage across disparate hardware that any workload can use.
A cloud storage strategy must acknowledge that storage is but one part of cloud use and involves storage and compute, as well as data that's accessible to all cloud resources.