AsmDB: Understanding and Mitigating Front-End Stalls in Warehouse-Scale Computers
It is well known that the datacenters hosting today's cloud services waste a significant number of cycles on front-end stalls. However, prior work has provided little insights about the source of these front-end stalls and how to address them. This work analyzes the cause of instruction cache m...
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| Veröffentlicht in: | IEEE MICRO 2020-05, Vol.40 (3), p.56-63 |
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| creator | Nagendra, Nayana Prasad Ayers, Grant August, David I. Cho, Hyoun Kyu Kanev, Svilen Kozyrakis, Christos Krishnamurthy, Trivikram Litz, Heiner Moseley, Tipp Ranganathan, Parthasarathy |
| description | It is well known that the datacenters hosting today's cloud services waste a significant number of cycles on front-end stalls. However, prior work has provided little insights about the source of these front-end stalls and how to address them. This work analyzes the cause of instruction cache misses at a fleet-wide scale and proposes a new compiler-driven software code prefetching strategy to reduce instruction caches misses by 90%. |
| doi_str_mv | 10.1109/MM.2020.2986212 |
| format | Article |
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| source | IEEE Electronic Library (IEL) |
| subjects | Cloud computing Complexity theory Data centers Hardware Optimization Prefetching Servers Warehouses |
| title | AsmDB: Understanding and Mitigating Front-End Stalls in Warehouse-Scale Computers |
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