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Parallella: an Open Multi-Core CPU Architecture

Posted by timothy on from the what's-your-use-case dept.

First time accepted submitter thrae writes "Adapteva has just released the architecture and software reference manuals for their many-core Epiphany processors. Adapteva's goal is to bring massively parallel programming to the masses with a sub-$100 16-core system and a sub-$200 64-core system. The architecture has advantages over GPUs in terms of future scaling and ease of use. Adapteva is planning to make the products open source. Ars Technica has a nice overview of the project."

6 of 103 comments (clear)

  1. Still very expensive for the performance by viperidaenz · · Score: 4, Informative

    and the architecture is also very limiting.

    16TFLOPS for $3000 or 0.09TFLOPS for $200. I'll stick to current hardware thanks. 178x more processing power for 15x more money. I would also prefer a "super computer" can address more than 4GB of RAM with more than 64bits of memory bandwidth. The architecture also limits the core cache to 64k.

    1. Re:Still very expensive for the performance by IAmR007 · · Score: 4, Informative

      I agree. 32 bit a PGAS memory model is silly. Giving each core its own 32 bit address space and using MPI for communication would be much more useful. Then, it could at least be a good learning tool for HPC programming techniques. Right now, it looks pretty useless.

      Even GPGPU is limited for what it can do for HPC. There's a lot more to HPC than raw mathematical power. Memory is often the bottleneck, not the FPUs. The reason we even deal with multiple processors is that the performance increase of single cores has nearly stalled, forcing the use of multiple processors. Communication between multiple cores/processors is a very complicated thing, as well, and getting good performance is a lot more complicated than hooking up a bunch of processors in a grid. For example, the supercomputer I work with has 90,112 2.3GHz cores and 90TB ram; 16 cores per chip in 704 blades, interconnected with a 3d torus network topology. It's the memory/cache size and speed and network topology that makes it a supercomputer. You could get the 800TFLOP/s in a much smaller package using GPUs, but the performance would be drastically less. Even with the 64 cores parallella could have, distributing the workload on a 64 core grid isn't easy. GPGPUs use work groups of smaller numbers of cores to make this sharing a bit more easy to manage. They should have at least made the interconnects a 2d torus rather than a grid, thereby reducing the maximum path length in half. In order to do stuff like quantum mechanics, a 5d torus is optimal. Memory access is the key. This is a bit like comparing apples to oranges, but that's exactly my point: the thing is not a supercomputer.

  2. Parallax Propeller by Y2K+is+bogus · · Score: 5, Informative

    The Parallax Propeller is a great multi-core chip to get started with. The chip is $7.95 and has 8 cores running at 80Mhz. You can pickup the Quickstart board at Radio Shack for $40, including an overpriced RS USB cable (they normally retail for $25).

    The Parallax Propeller is a much more economical way of getting started with multi-core programming. Parallax offers the PropTool, which provides SPIN and PASM language support. For C development you can get SimpleIDE which is a great IDE to get started with C programming on the Propeller, which uses a port of GCC.

  3. Re:Hmmm... by viperidaenz · · Score: 4, Informative

    If you've got $100 to spare, a Radeon 7750 provides over 800GFLOPS. If you've got more money a 7970 will give you 4.3TFLOPS for $550.
    a GTX650 will give you 800GFLOPS for $100 and a GTX680 will give you 3TFLOPS for $500.

  4. Re:Comparisons... by ssam · · Score: 4, Interesting

    the devboard has a Dual-core ARM A9, so more like a pandaboard. even if you ignore the co-processor they are offering a lot for $99.

    its interesting to compare the epiphany processor to a GPU. both give you lots of cores, GPUs get up ino the hundreds, epiphany is meant to scale to 4000. But a GPU is highly opitmised for graphics, and applying identical operations to millions of data values. in a GPU groups of core (typically 32) operate as a wavefront, if the code branches on an if stament, then the cores that get the else branch have to wait until the ones that follow the if finish.

    epiphany has independant cores. you can send them each a different program. so for a much wider set of algorithms you can get efficient speedups. in a way it is more like the xeon phi, but without making each core a full x86 compatible processor.

  5. Re:Kickstarter by naeger · · Score: 4, Informative

    I really like the parallella project. Due to its low power consumption (2 watts for the 64-core version), it is the only option to bring significant processing power to mobile devices (e.g. mobile robots/quadrocopter/drones) and would be ideally suited to implement machine vision and neural network/machine learning algorithms for those mobile devices.

    That said, their kickstarter initiative has some serious flaws:

    1. They are only offering the 16-core version for a goal of $750k. The much more interesting 64-core version is available only if a whopping $3m goal is met. Way out of reach for such a specialized interest project. And everyone who reads information about the parallella reads about the "sexy" 64-core version everywhere but can only fund the "just nice" 16-core version. From the comments it is clear: everyone wants the 64-core version.
    2. There is only one interesting pledge: $99 for the 16-core version. No addons. No extras etc.
    3. The information from adapteva is lacking. Only today they made the documentation available. But still there are no demos and dozens of questions in the comments which are unaswered.

    Compare this to a greatly successful campaign like for example the Digispark (a low cost "mini-arduino"): a lower easily reachable goal, lots and lots of extras and addons developed together and in response to the backers and a constant information and communication with the backers. I wanted to spend $20 on this project but finally spent $70 because of all the addons and how responsive the team was to the backers. Digispark achieved more than 6000% of its initial goal!

    That said, what would I suggest for the Parallella kickstarter:

    1. Go for the 64-core version. Bring the goal from $3m down to say $1.5m by dropping the 16-core version (should save almos $1m) and some bank loan (if you can present >1000 backers who pay >$1.5m that should be no problem.
    2. Offer more than just a 64-core parallella for $199. Offer special version for a higher price. Offer a dual-64-core version (with two epiphanies on it). Offer a "compute cluster": a little laser cut box with a network, a power supply and slots for up to 8 parallellas. Offer those cluster equipped with 1-8 parallellas. Offer a "machine vision" parallella with a camera sensor attached to it .. and so on ....
    3. Be more open and communicating with the community. Answer all questions in the comments. Put up some polls what backers want. Provide demos/tutorials etc.

    Please don't take this personally. But i would really like to see this project succeed. .... and I want machine vision and a neural network brain for my quadrocopter (yep, world domination ... that's the plan!) ;)