A decade ago, Fangjin “FJ” Yang was a software architect at startup Metamarkets, a company that was building a user-facing analytics engine that a lot of developers simultaneously could go to, click on a UI, and very quickly get answers to their questions. …
To catch a glimpse of the future of what memory devices and approaches will dominate the AI-centric datacenter, there are few better forecasters than Evangelos Eleftheriou. …
It is probably a myth that Bill Gates said “640 KB ought to be enough,” and whether or not he said it the truth is that it has never been enough. …
Supercomputer maker SGI has been going it alone in the upper echelons of the computing arena for decades and has brought much innovation to bear on some of the most intractable simulation, modeling, and analytics problems in the world. …
When supercomputer maker SGI tweaked its NUMA server technology to try to pursue sales in the datacenter, the plan was not to go it alone but rather to partner with the makers of workhorse Xeon servers that did not – and would not – make their own big iron but who nonetheless want to sell high-end machines to their customers. …
Hyperscalers and the academics that often do work with them have invented a slew of distributed computing methods and frameworks to get around the problem of scaling up shared memory systems based on symmetric multiprocessing (SMP) or non-uniform memory access (NUMA) techniques that have been in the systems market for decades. …
It is almost without question that search engine giant Google has the most sophisticated and scalable data analytics platform on the planet. …
These days when you talk to people in the tech industry, you will get the idea that in-memory computing solves everything. …
As noted at the beginning of this article series last week, an initial dive into in-memory computing meant questioning whether this was just another of those buzz words or whether there was some meat behind it. …
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