"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."
But the real challenge is in parallelizing the algorithms, reducing data dependencies, and so on. I can get my feet wet with parallel processing on a multi-core PC just fine; making a program run efficiently in parallel is an entirely different challenge, and I don't see how this platform can help me do that.
"I can get my feet wet with parallel processing on a multi-core PC just fine"
No, you can't, unless you pay severals orders of magnitude more than $99. (Affordable)Multi core today means 2,4 cores at most . You can get your feet wet with the graphics card though. I did, and this is the reason I'm backing this project.
Parallel computing is a different paradigm that serial, in fact is almost the opposite, instead of a big central memory you program for small distributed blocks of memory. Taking this into account means x200 faster than just not.
Once you have a parallel design you can change it for different platforms or even hardware.(witch is parallel by nature), very easy. But you need a platform that is flexible(more than FPGAs) and near to software tools enough for testing and this is great.
But the real challenge is in parallelizing the algorithms, reducing data dependencies, and so on. I can get my feet wet with parallel processing on a multi-core PC just fine; making a program run efficiently in parallel is an entirely different challenge, and I don't see how this platform can help me do that.