Abstract: The economics of Moore's Law are stumbling, so vendors of many-core architectures are transitioning from single-die monolithic designs to multi-chiplet disintegrated systems within a package. Disintegration lowers cost for the same number of cores but bottlenecks the interconnect. Ideally, disintegration should increase performance per dollar: cost savings should outweigh the disintegration slowdown. Although industry has reported cost savings, the performance penalty of disintegration is not well studied.This paper presents the first characterization, to our knowledge, of disintegration performance penalty across a diverse suite of applications. Unsurprisingly, applications with high speedups on monolithic systems continue to scale well on disintegrated systems, and vice versa. However, the disintegration slowdown compared to an equivalently sized monolith exhibits high variance across applications, with some achieving just over half the performance. Why do some applications get a performance per dollar win, while others lose? Through regression analysis, we find that metrics relating to the network-on-package bandwidth and data sharing correlate with disintegration slowdown. Programmers were already cautioned against shared mutable data on monolithic systems, yet data sharing is unavoidable in many applications. These applications will be disproportionately harmed in the disintegrated future.
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