Adapteva Parallella Supercomputing Boards Start Shipping 98
hypnosec writes "Adapteva has started shipping its $99 Parallella parallel processing single-board supercomputer to initial Kickstarter backers. Parallella is powered by Adapteva's 16-core and 64-core Epiphany multicore processors that are meant for parallel computing unlike other commercial off-the-shelf (COTS) devices like Raspberry Pi that don't support parallel computing natively. The first model to be shipped has the following specifications: a Zynq-7020 dual-core ARM A9 CPU complemented with Epiphany Multicore Accelerator (16 or 64 cores), 1GB RAM, MicroSD Card, two USB 2.0 ports, optional four expansion connectors, Ethernet, and an HDMI port."
They are also releasing documentation, examples, and an SDK (brief overview, it's Free Software too). And the device runs GNU/Linux for the non-parallel parts (Ubuntu is the suggested distribution).
Re:Tiny but useful? (Score:4, Informative)
half the Gflops, 64 cores, 80% lower cost, 5 watts (Score:4, Informative)
It uses 5-10 watts, whereas the Core i7 uses 100 - 200 watts, with the chipset.
So total cost of ownership is about 90% less than the Core i7. Ten of them would spank the heck out of a Core i7 and cost the same.
> and what can you run on it ?
16 or 64 cores is good for facial recognition, audio processing, video processing, some network stuff - things where you run the same function on many pixels / samples / rows. So for face recognition, for example, the image would be broken up into 64 blocks and all of the blocks analyzed simultaneously on the 64 cores.
A database designed for the many cores could work well. For example, say you need to sort a table with 100,000 rows. On a system like this with 64 cores,
each core could simultaneously sort a group of 1,500 rows, then you'd merge those 64 sorted groups together ala merge sort. As a firewall, it could handle a blacklist with a million entries, as each core would handle simultaneously apply 1/64 of that list.
Re:half the Gflops, 64 cores, 80% lower cost, 5 wa (Score:5, Informative)
Yeah but compare it to a GPGPU and you start to realize how slow it is, a $200 660 GTX does 1880 GFLOPS in 140W.
1 GFLOPS/$ versus 9.4 GFLOPS/$
10 GFLOPS/Watt versus 13.4 GFLOPS/Watt