Parallella and Adapteva

By Massimiliano Versace | September 28, 2012

Adapteva, a company that was on Neurdon's radar for a while, is launching their new Parallella project. The end goal is to make parallel computing, including the sort of massively parallel computing neural modelers need, both easy and cheap. And we like both...

From their Kickstarter initiative:

"Making parallel computing easy to use has been described as "a problem as hard as any that computer science has faced". With such a big challenge ahead, we need to make sure that every programmer has access to cheap and open parallel hardware and development tools. Inspired by great hardware communities like Raspberry Pi and Arduino, we see a critical need for a truly open, high-performance computing platform that will close the knowledge gap in parallel programing. The goal of the Parallella project is to democratize access to parallel computing. If we can pull this off, who knows what kind of breakthrough applications could arise. Maybe some of them will even change the world in some small but positive way.

The Parallella Computing Platform

To make parallel computing ubiquitous, developers need access to a platform that is affordable, open, and easy to use. The goal of the Parallella project is to provide such a platform! The Parallella platform will be built on the following principles:

-Open Access: Absolutely no NDAs or special access needed! All architecture and SDK documents will be published on the web as soon as the kickstarter project is funded.

- Open Source: The Parallella platform will be based on free open source development tools and libraries. All board design files will be provided as open source once the Parallella boards are released.

- Affordability: Hardware costs and SDK costs have always been a a huge barrier to entry for developers looking to develop high performance applications. Our goal is to bring the Parallella high performance computer cost below $100, making it an affordable platform for all.

The Parallella platform is based on the Epiphany multicore chips developed by Adapteva over the last 4 years and field tested since May 2011. The Epiphany chips consists of a scalable array of simple RISC processors programmable in C/C++ connected together with a fast on chip network within a single shared memory architecture. Much more detailed technical information about the Epiphany architecture can be found on Adapteva's web site.

Go to kickstarter

About Massimiliano Versace

Massimiliano Versace is the director of the Boston University Neuromorphics Lab. The lab focuses on the study of biological intelligence with the goal of embedding the derived fundamental principles in bio-inspired computers and robots. His research interests are focused on neural networks – in particular applied to spiking-based neural models of learning and memory in the cerebral cortex. With a few colleagues, he founded Neurala LLC in 2006 to commercialize brain-based software. For more info, visit his website

4 Responses to Parallella and Adapteva

  1. zeev says:

    funny that you posted this. it does seem interesting, more for its crowdsourcing efforts than the underlying ideas, which could just as easily be fully funded if there were the right sized grant for it.

    any thoughts on this memristor development?
    http://phys.org/news/2012-10-ferroelectric-memristors-brain-like.html

  2. vv111y says:

    Hi Massimilliano,

    Great to see you on the promo video and helping out. I’m a backer, and your endorsement helped. Couple things:

    1) since you have access to true neuromorphic hardware, why do you see this all digital solution as still worthwhile?

    2) they’re having trouble and getting some criticism – one is that GPUs are more cost effective when you scale, which is true. I assume that when they bring out their 1000+cores boards that they will then be directly competing against GPUs. Also there is bad press such as this http://www.extremetech.com/electronics/137085-adapteva-turns-to-kickstarter-to-fund-massively-parallel-processor. It’s the lack of memory and throughput to the cores. What’s your take on these criticisms?

  3. Hi Willi,

    thanks for your comment. Quick reply
    1) we do work on both fronts. Digital is nice since we are doing research in many areas, and the flexibility of digital is insurmountable at least at the stage of experimentation.
    2) I see some of those points, and at the end of the day it really depends how your OS takes advantage of the multiple cores by appropriately distributing the threads to the many cores. This is pretty much an active area of investigation for us, and that’s why we want to support and hopefully play with their architecture.

    Max

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