Wlakiz on 06 December 2012
as someone who has done CUDA programming, I can tell you that GPGPU programming no easier than using cell. Objects needs to be copied to the GPU's memory, which could range from fast but small local memory to the slow but larger shared memory. When you copy back, the memory needs to coalesced to achieve optimal write performance. Not to mention, you need to manage and sync warps (cluster of threads) which can cause huge bottlenecks if you require all data before sending stuff back to the main memory.
Of course, this is all from 3 years ago.. not sure how GPGPU programming changed these days.
