People tend to obsess about processing when it comes to system design, but ultimately an application and its data lives in memory and anything that can improve the capacity, throughput, and latency of memory will make all the processing you throw at it result in useful work rather than wasted clock cycles. …
As data grows, a shift in computing paradigm is underway. I started my professional career in the 1990s, during massive shift from mainframe computing to the heyday of client/server computing and enterprise applications such as ERP, CRM, and human resources software. …
In the public cloud business, scale is everything – hyper, in fact – and having too many different kinds of compute, storage, or networking makes support more complex and investment in infrastructure more costly. …
Oil and natural resource discovery and production is an incredibly risky endeavor, with the cost of simply finding a new barrel of oil tripling over the last ten years. …
When it comes to deep learning innovation on the hardware front, few other research centers have been as forthcoming with their results as Baidu. …
If you want to study how datacenter design has changed over the past two decades, a good place to visit is Quincy, Washington. …
What is good for the simulation and the machine learning is, as it turns out, also good for the database. …
It’s elastic! It’s on-demand! It scales dynamically to meet your needs! …
One of the reasons why Dell spent $60 billion on the EMC-VMware conglomerate was to become the top supplier of infrastructure in the corporate datacenter. …
The jury is still out when it comes to how wide-ranging the application set and market potential for quantum computing will be. …
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