[pradn]

1) Amdahl's law means it's not useful to have hundreds of cores for general purpose computing. There's not that much parallel work to do in typical applications. Increasing the proportion of work that's parallelizable for a given application pays dividends when you have more cores - that's why Servo is so exciting. In some cases, picking an O(n2) algorithm that's easy to parallelize will be faster than a less parallizable O(nlog(n)) algorithm - this is true for problems like Single-Source Shortest Paths (SSSP).

2) Shared resources (in-memory mutable data, hardware devices) mean the ratio of contention to CPU work goes up when you have more cores.

3) Cores on a single die need to share the same constraints - thermal limits and transistor count. So you're best off having enough powerful cores to get you to a sweet spot of single-core performance vs multi-core parallelism.

4) It's hard to provide a performant and useful many-core machine model. Cache coherence makes it easier to program a many-core machine, but limits performance. Without it, you're stuck with distributed systems-style problems.