The problems we have looked at over the course of the NESS project vary in terms of computational requirements. Some lead to code which will not run in anywhere near real time on a typical single core microprocessor… others are easily real-time even in relatively modest hardware!
For this reason, we’ve explored parallel architectures, such as graphics processing units (GPUs), which can allow much greater computation rates than typical microprocessors—provided that one’s algorithm is readily parallelizable! From their origins in graphics rendering and games, GPUs are rapidly taking on the role that the supercomputers used to play, across a wide range of heavy computational problems. But there are other types of parallelism that we’ve made use of (sometimes in conjunction with GPUs), including work in multicore annd low-level vector intrinsics. For much more on this, see the dedicated Acceleration page.
There has recently been some exploration of GPUs in 3D room acoustics and a large part of the NESS project is to both extend this work, and also to look at GPU use for more general systems in acoustics and audio. We want to be able to listen to the sounds we produce in a reasonable amount of time (if not real time!). We’ve had some success with this; see the Virtual Room Acoustics page. We’re happy to announce that this work will continue under an ERC Proof of Concept grant, starting in December 2016 (as I type this!).
