The Ripple Effect

9 Ways to Press the Easy Button for Scalability

Multiprocessor, TidalScale, in-memory, big data, software-defined server

In some recent blogs, we covered eight reasons why Software-Defined Servers can help reduce OpEx and CapEx, while helping data center managers extract maximum use and value from existing IT resources. And last week, we illustrated how you can achieve some startling real-world performance gains by implementing Software-Defined Servers.

Today, let’s look at how simple, straightforward and transparent Software-Defined Servers are. 

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Focus on Possibilities, Not Limits

Large memory, Amdahl, Gustafson, Multiprocessor, TidalScale

Computer Science is obsessed with "negative results" and "limits.” We seem to delight in pinpointing a terminus for virtually any technology or architecture – to map the place where the party ends.

Take, for example, Amdahl's Law, which seems to suggest that once you reach a certain point, parallelism doesn't help performance. Amdahl’s law has prevented many from believing that a market exists for bigger single systems since, since the law leads us to conclude larger multicore systems won't solve today's problems any faster.

Beware the Intuitively Obvious

The reasoning behind Amdahl’s Law turns on an assumption that all the parts of the problem must interact in such a way that

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TidalScale featured in e-week!
Gary Smeardon in the Cube Interview