Swim In Data At The Edge, Don’t Drown In It In the Datacenter
Analytics systems have been downing in data for years, and the edge is going to flood it unless the architecture changes. …
Analytics systems have been downing in data for years, and the edge is going to flood it unless the architecture changes. …
When looking for all-flash storage arrays, there is no lack of options. …
The European Union has never been willing to cede the exascale computing race to the United States, Japan, or China. …
For the past several years, machine learning as evolved by the hyperscalers has been trickling down from on high, through frameworks and services, into enterprises. …
Hyperconverged storage is a hot commodity right now. Enterprises want to dump their disk arrays and get an easier and less costly way to scale the capacity and performance of their storage to keep up with application demands. …
Hyperconverged infrastructure in some ways is like the credit card in those old TV ads: in this case, it’s everywhere that enterprises want to be. …
Nvidia caused a shift in high-end computing more than a decade ago when it introduced its general-purpose GPUs and CUDA development platform to work with CPUs to increase the performance of compute-intensive workloads in HPC and other environments and drive greater energy efficiencies in datacenters. …
Amazon Web Services essentially sparked the public cloud race a dozen years ago when it first launched the Elastic Compute Cloud (EC2) service and then in short order the Simple Storage Service (S3), giving enterprises access to the large amount compute and storage resources that its giant retail business leaned on. …
Enterprises can see cost and efficiency benefits when they migrate workloads into the cloud, but such moves also come with their share of challenges in complexity and management. …
There continues to be an ongoing push among tech vendors to bring artificial intelligence (AI) and its various components – including deep learning and machine learning – to the enterprise. …
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