Jack Ganssle wrote a column about the failure of multicore to scale, based on an article in IEEE Spectrum. He makes the following claim:
Now a study in IEEE Spectrum shows that even for the classic embarrassingly parallel problems like weather simulations multicore offers little benefit. The curve in that article is priceless. As the number of cores grow from two to 64 performance plummets by a factor of five. Additional processors nullify each other.
Call it the Nulticore Effect.
I think that Jack misunderstood some of the article. What it really says, as far as I can tell, is that certain types of applications will have problems with the lower external memory bandwidth per core afforded by a 16-way or 32-way multicore based on traditional processor architectures.
As I read it, regular classic “embarrassingly parallel” (or as Grant Martin would say, “proudly parallel”) problems can be handled by managing data location and computation location carefully to colocate data and code, which lends itself to on-chip caching and probably also local-memory architectures.
When other problems that are less regular are going to run into the memory bandwidth wall:
But an increasing number of important science and engineering problems—not to mention national security problems—are of a different sort. These fall under the general category of informatics and include calculating what happens to a transportation network during a natural disaster and searching for patterns that predict terrorist attacks or nuclear proliferation failures. These operations often require sifting through enormous databases of information.
So while I think the Sandia people have a very good point to make, it is not the end of the usefulness of multicore. It is only the case for bandwidth-intense irregular algorithms, while many systems today make good use of hundreds of cores without a problem. Also, the research in IEEE Spectrum proposes a solution in the form of stacked memory — so what we really have is a bit of PR for a particular kind of architecture…