>I and a few others were of the opinion that the scientific community didn't build the equivalent of LinPack or scientific simulation packages on 'Google like' architectures because they didn't have access to such architectures rather they had "Beowulf" clusters [2] which had been built to be more like Supercomputers. It wasn't that such problems couldn't be worked on shared nothing architectures, it was just that nobody was making any real progress along those lines.
Whats is the difference between 'Google like' and Beowulf or other similar Linux clusters for scientific calculations? A Beowulf is just a software which clusters together a bunch of cheap computers connected by whatever Ethernet is currently available for normal money (of course you can throw more money if you have it). On the other side, people have no problem running physics or bioinformatics calculations onto hundreds of Amazon nodes.
>it would put a huge crimp in any supercomputer type system.
thats what Beowulf and the likes already did 10 years ago. It is one of the reasons why "supercomputers" (SMP nodes connected by extremely fast backplanes in big cabinets or as you said "lots of shared state and epic low latency bandwidth") had the low rate of survival into 21st century. Of course there is still Top500 supercomputers - big rooms with a lot of racks and, frequently, very expensive/fast networks. Yet, if your distributed program significantly depends on the speed of the interconnect, ie. it have significant message passing component, it usually wouldn't scale effectively, ie. it may scale, yet with quickly diminishing return, Amdahl law style, even with extremely low latency / expensive interconnect.
Whats is the difference between 'Google like' and Beowulf or other similar Linux clusters for scientific calculations? A Beowulf is just a software which clusters together a bunch of cheap computers connected by whatever Ethernet is currently available for normal money (of course you can throw more money if you have it). On the other side, people have no problem running physics or bioinformatics calculations onto hundreds of Amazon nodes.
>it would put a huge crimp in any supercomputer type system.
thats what Beowulf and the likes already did 10 years ago. It is one of the reasons why "supercomputers" (SMP nodes connected by extremely fast backplanes in big cabinets or as you said "lots of shared state and epic low latency bandwidth") had the low rate of survival into 21st century. Of course there is still Top500 supercomputers - big rooms with a lot of racks and, frequently, very expensive/fast networks. Yet, if your distributed program significantly depends on the speed of the interconnect, ie. it have significant message passing component, it usually wouldn't scale effectively, ie. it may scale, yet with quickly diminishing return, Amdahl law style, even with extremely low latency / expensive interconnect.