It’s been a long wait, about four years if memory serves me well, since Intel introduced the Xeon E7, a high-end server CPU targeted at the highest performance per-socket x86, from high-end two socket servers to 8-socket servers with tons of memory and lots of I/O. In the ensuing four years (an eternity in a world where annual product cycles are considered the norm), subsequent generations of lesser Xeons, most recently culminating in the latest generation 22 nm Xeon E5 V2 Ivy Bridge server CPUs, have somewhat diluted the value proposition of the original E7.
So what is the poor high-end server user with really demanding single-image workloads to do? The answer was to wait for the Xeon E7 V2, and at first glance, it appears that the wait was worth it. High-end CPUs take longer to develop than lower-end products, and in my opinion Intel made the right decision to skip the previous generation 22nm Sandy Bridge architecture and go to Ivy Bridge, it’s architectural successor in the Intel “Tick-Tock” cycle of new process, then new architecture.
What was announced?
The announcement was the formal unveiling of the Xeon E7 V2 CPU, available in multiple performance bins with anywhere from 8 to 15 cores per socket. Critical specifications include:
Up to 15 cores per socket
24 DIMM slots, allowing up to 1.5 TB of memory with 64 GB DIMMs
Approximately 4X I/O bandwidth improvement
New RAS features, including low-level memory controller modes optimized for either high-availability or performance mode (BIOS option), enhanced error recovery and soft-error reporting
Improving the use of data and analytics is a top strategic priority for many companies. But organizations face major challenges ramping up their information management capabilities — in particular due to the combination of a brutal proliferation of new or enhanced technologies, emerging data sources, and difficulty in finding skilled people with the appropriate experience. As a result, companies are increasingly looking to service providers for help.
Please note that we use the term “data services” to refer to broader engagements (including data delivery, analysis, management, or governance-related services), while “data management services” form a smaller subset of services relating to finding, collecting, migrating, and integrating data.
Here are three of the key findings from our research:
More than two-thirds of organizations expect their spending on data management services to increase; 41% stated they expect spending to increase 5% to 10% in the next 12 months.