Another Word For It Patrick Durusau on Topic Maps and Semantic Diversity

August 1, 2013

Parallella is Shipping!

Filed under: Parallel Programming,Parallela — Patrick Durusau @ 2:45 pm

Creating a $99 parallel computing machine is just as hard as it sounds by Jon Brodkin.

From the post:

Ten months ago, the chipmaker Adapteva unveiled a bold quest—to create a Raspberry Pi-sized computer that can perform the same types of tasks typically reserved for supercomputers. And… they wanted to sell it for only $99. A successful Kickstarter project raised nearly $900,000 for the so-called “Parallella,” and the company got to work with a goal of shipping the first devices by February 2013 and the rest by May 2013.

As so often happens, the deadlines slipped, but Adapteva has done what it set out to do. Last week, the company shipped the first 40 Parallellas and says it will ship all 6,300 computers ordered through the Kickstarter by the end of August. Anyone who didn’t back the Kickstarter can now pre-order for delivery in October.

The first version of the board was finished in January, but it cost $150 to produce. “After that it was iterating time after time to get the bill of materials down to something we wouldn’t be losing $50 per board on,” Adapteva CEO and founder Andreas Olofsson told Ars.

Adapteva called Parallella “A Supercomputer For Everyone” in the title of its Kickstarter. Of course, each individual Parallella computer is not a supercomputer in and of itself. But each is capable of the types of parallel computing tasks performed by supercomputers—on a smaller scale—and they can be joined together in Ethernet-connected clusters to create something resembling a supercomputer, Adapteva says.

(…)

Parallella is open source hardware, meaning Adapteva released all the details about the components to the public. Board design files are on GitHub, for example. Theoretically, companies besides Adapteva could build Parallella computers.

See the post for details but there is a higher priced 64-bit chip as well.

Thoughts about parallel processing of topic maps?

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