In this paper, we explore the challenges in scaling on-chip networks towards kilo-core processors. Current low-radix topologies optimize for fast local communication, but do not scale well to kilo-core systems because of the large number of routers required. These increase both power and hop count. In contrast, symmetric high-radix topologies optimize for global communication with fewer hop counts, but degrade local communication with their large, slow routers. To address both local and global communication optimizations independently, we decouple the interconnect design using asymmetric high-radix topologies. By setting a design goal of matching rauter speed with wire speed, our praposed topologies use fast medium-radix rauters to optimize for local communication and a few slow high-radix rauters that reduce hop count to optimize for global communication. Our asymmetric high-radix designs are enabled by recently praposed SwizzleSwitches, which allow us to achieve peiformance scalability within realistic power budgets. We prapose and evaluate two asymmetric high-radix topologies: Super-Star (asymmetric folded Clos) and Super-StarX (asymmetric folded Clos with superimposed mesh). Our evaluations show that the best performing asymmetric high-radix topology improves average network latency over a mesh by 45% while reducing the power consumption by 40%. When compared to symmetric high-radix topologies network thraughput is improved by 2.9× while still praviding similar latency benefits and power ejficiency.

With multi-core processors now mainstream, the shift to many-core processors poses a new set of design challenges. In particular, the scalability of coherence protocols remains a significant challenge. While complex Network-on-Chip interconnect fabrics have been proposed and in some cases implemented, most of industry has slowly evolved existing coherence solutions to meet the needs of a growing number of cores. Industries' slow adoption of Network-on-Chip designs is in large part due to the significant effort needed to design and verify the system. However, simply scaling bus-based coherence is not straightforward either because of increased contention and latency on the bus for large core counts.

Supply voltage scaling has stagnated in recent technology nodes, leading to so-called "dark silicon." In this paper, we investigate the limit of voltage scaling together with task parallelization to maintain task completion latency. When accounting for parallelization overheads, minimum task energy is obtained at "near threshold" supply-voltages across 6 commercial technology nodes and provides 4X improvement in overall CMP performance.