I've written code for a few different large-scale SSI architectures. The shared-memory programming model is less efficient than explicit message passing in prac

I've written code for a few different large-scale SSI architectures. The shared-memory programming model is less efficient than explicit message passing in practice because it is much more difficult to optimize. The underlying infrastructure is essentially converged at this point, so performance mostly comes down to the usability of the programming model. The marketing for SSI was that it was simple because programmers would not have to learn explicit message passing. Unfortunately, people that buy supercomputers tend to care about performance, so designing a supercomputer that is difficult to optimize misses the point. In real code, the only way to make them perform well was to layer topology-aware message passing on top of the shared memory model. At which point you should've just bought a message passing architecture. There is only one type of large-scale SSI architecture that is able to somewhat maintain the illusion of uniform shared memory -- hardware latency-hiding e.g. barrel processors. If programmers have difficulty writing scalable code with message passing, then they definitely are going to struggle with this. These systems use a completely foreign programming paradigm that looks deceptively like vanilla C++. Exceptional efficient, and companies design new ones every few years, but without programmers that grok how to write optimal code they aren't much use.