In previous Cloud Optimized Storage Solution articles, I’ve discussed the content being stored, the method of storage, as well as principles derived from data tiering. Today, I want to jump ahead a bit and discuss how neural networks and heuristics can impact the processing of object and file data for the cloud.
One of the more recent advancements within computing has been the application of heuristics and neural networking. Heuristics is defined as being “…an educational method in which learning takes place through discoveries that result from investigations…“ While heuristics has historically been used in such products like anti-virus software, it provides an incredible wealth of capability and technology for the COSS solution. Similarly, neural networks provide capacitive understanding of processing layers and optimizations that learn patterns based on underlying statistical data. How do these two technologies apply to COSS?
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In developing the Future Storage System series, I have been trying to take a part of my excitement for storage technologies and overlay them with systems/platform technology. Typically, the storage industry lags on the platform development side of the house (mostly out of necessity). So, part of looking at the Future Storage System was to take into consideration that in the basic design, some of the more current technologies could and should be used to enable “forward” thinking. That’s why you see such a heavy emphasis on Torrenza, Hypertransport, and integrated memory controllers. With the exception of Torrenza, each of the other aspects of system design have a rich history. Hypertransport, arguably, has been an outlier on the bus technology side, but it’s capabilities and industry support are unparalleled. Integrated memory controllers, while “nothing new” (DEC Alpha, anyone?) really came to the for when AMD introduced them as part of the Athlon series of processors. Today, I’d like to toss another wrinkle into the “platform meets storage” discussion by including another developing technology: the GPU (Graphical Processing Unit).
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