> I think easily and uniformly programming disparate compute devices (CPUs, SIMD, GPUs, FPGAs, ISPs, DSPs, and eventually quantum) is the next BIG problem in pr

> I think easily and uniformly programming disparate compute devices (CPUs, SIMD, GPUs, FPGAs, ISPs, DSPs, and eventually quantum) is the next BIG problem in programming languages. The biggest challenge to producing a unified programming model across all of these is dealing with moving data around. CPU vs GPU vs FPGA all have very different memory access characteristics. Gary Sabot was the first to try to tackle the problem of dealing with memory layout/locality in a language with what he called the Paralation model (http://www.amazon.com/The-Paralation-Model-Architecture-Independent-Intelligence/dp/0262192772 http://www.amazon.com/The-Paralation-Model-Architecture-Inde...) and a lot of that work carried over into NESL (http://www.cs.cmu.edu/~scandal/nesl.html http://www.cs.cmu.edu/~scandal/nesl.html). Hadoop is a very lobotomized and hard to use modern version of these ideas. I wouldn't knock DSLs - a lot of people are having good results using DSLs to program FPGAs (for example that's pretty much what http://www.novasparks.com/ http://www.novasparks.com/ does - http://lisp-univ-etc.blogspot.com/2013/06/lisp-hackers-marc-battyani.html http://lisp-univ-etc.blogspot.com/2013/06/lisp-hackers-marc-...).