Indeed, power is the key differentiator. This processor was designed for embedded applications.
Nvidia C2050 479W/TFlop
At BlueGene/Q scale that would reduce power consumption to around 1MW (from 8MW), saving around $7M in annual running costs at wholesale electricity prices.
As an investor, I would not invest in them for the following reasons:
First, the economics don't make sense. Take Nvidia's Tesla as a comparison point:
Nvidia Tesla C2050 (~1TFLOP for ~$1900) = 1.9 $dollar/GFLOP
and Parallella is proposing 90 GFLOPs for $199 = 2.2 $dollars/GFLOP
You can't enter a market place and not be compelling on the price/performance curve as compared to the competition.
Second, You can't add cores without keeping them busy, which means significant memory bandwidth must be supplied. This is the biggest issue when it comes to multi-core computer performance. It's interesting that they say nothing about memory or memory bandwith.
Third, History hasn't been kind to multicore startups. Take the 2008 article:
Five Multicore Chip Startups to Watch
Only one still in existance?
What this really could become is a small subunit of a massively parallel supercomputer. By itself, it is not a supercomputer!
I agree the title is misleading but I laud the developers efforts.
Please stop calling it a supercomputer.
90 GFLOPS is not even close to 16.32 petaflops (IBM BlueGene/Q - June 2012 fastest Top500)
This is like saying that someone is building a Formula One equivalent race car that can travel 230 miles in 20.7 years (instead of an hour).
A tech reporter should know better, so stop propagating misperceptions....
What are the engineering and design challenges in creating successful IoT devices? These devices are usually small, resource-constrained electronics designed to sense, collect, send, and/or interpret data. Some of the devices need to be smart enough to act upon data in real time, 24/7. Specifically the guests will discuss sensors, security, and lessons from IoT deployments.