Come on Stacey, get off your couch and take a look at what people are really going to do with such a computer. NOBODY is going to buy a $20,000 machine and write Python code to spice up family picnic movies. LAZY journalism!

Gedae is centered around the idea of using a high level language to specify your algorithm without defining how it will be implemented on the hardware. After the algorithm is defined the developer chooses a platform and says I want my software implemented this way for this architecture. The compiler takes all that information and creates an optimized version of the software for the chosen architecture. By maintaining the generality of the application and automatically handling the details of the multiprocessor/multicore implementation the user gets:
- a portable algorithm
- a very efficient implementation of that algorithm for a chosen architecture
- with no requirement to learn specialized techniques for a particular architecture.

I know this is self promotion, but we are a company of engineers who generally keep our heads down and let the technology speak for us. It has led to slow expansion but very devoted users. IBM compared Gedae to the majority of the tools mentioned in this article and Gedae came out the clear winner. Most of these companies get a lot of press because of VC money but most also have little substance behind the technology. Many of the concepts these guys are pushing were tried and failed in the A and D market by other companies long ago.

Yeah I definitely agree. There is no single solution to the sequential-parallel transition. We should start looking at a dependency based model. Datarush, a multi-core java library, is also one of those new companies to watch. They use a flow based approach which emphasizes dependencies. A great niche solution for problems easily viewed from a data perspective.

http://www.cilk.com/multicore-e-book/

That said, it’s reasonable to expect the emergence of a de facto standard within each segment. For example, Cilk Arts is betting that for mainstream C++ programmers who want to maintain the serial semantics of their existing apps, Cilk++ will deliver a winning solution.

I also suspect that there won’t be one dominant parallel programming architecture. And, of course, meshes have been around a long time (e.g. Transputer), although IIRC Tilera claims to have better software.

FPGA’s are also in the mix. If you can afford the license fees, National Instruments has software to program FPGA’s using LabView. There are C to FPGA compilers.