Philip M Wells
Philip is a software engineer at Google working on next-generation systems architecture for the Google Platforms group. His interests include distributed systems design, microarchitecture, virtualization, and simulation. Philip received a Ph.D. in Computer Science from the University of Wisconsin-Madison.
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Energy Proportional Datacenter Networks
Dennis Abts
Peter Klausler
Proceedings of the International Symposium on Computer Architecture, ACM (2010), pp. 338-347
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Numerous studies have shown that datacenter computers rarely operate at full utilization, leading to a number of proposals for creating servers that are energy proportional with respect to the computation that they are performing. In this paper, we show that as servers themselves become more energy proportional, the datacenter network can become a significant fraction (up to 50%) of cluster power. In this paper we propose several ways to design a high-performance datacenter network whose power consumption is more proportional to the amount of traffic it is moving --- that is, we propose energy proportional datacenter networks.
We first show that a flattened butterfly topology itself is inherently more power efficient than the other commonly proposed topology for high-performance datacenter networks. We then exploit the characteristics of modern plesiochronous links to adjust their power and performance envelopes dynamically. Using a network simulator, driven by both synthetic workloads and production datacenter traces, we characterize and understand design tradeoffs, and demonstrate an 85% reduction in power --- which approaches the ideal energy-proportionality of the network.
Our results also demonstrate two challenges for the designers of future network switches: 1) We show that there is a significant power advantage to having independent control of each unidirectional channel comprising a network link, since many traffic patterns show very asymmetric use, and 2) system designers should work to optimize the high-speed channel designs to be more energy efficient by choosing optimal data rate and equalization technology. Given these assumptions, we demonstrate that energy proportional datacenter communication is indeed possible.
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Dynamic Heterogeneity and the Need for Multicore Virtualization
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Koushik Chakraborty
Gurindar S Sohi
ACM SIGOPS Operating Systems Review, vol. 43 (2009), pp. 5-14
Mixed-Mode Multicore Reliability
Koushik Chakraborty
Gurindar S. Sohi
Proceeding of the 14th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), ACM (2009), pp. 169-180
Adapting to Intermittent Faults in Multicore Systems
Koushik Chakraborty
Gurindar S. Sohi
Proc. of the 13th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS) (2008), pp. 255-264
Adapting to Dynamic Heterogeneity: Virtualization for the Multicore Era
Ph.D. Thesis, University of Wisconsin-Madison (2008)
Serializing Instruction in System-Intensive Workloads: Amdahl's Law Strikes Again
Gurindar S. Sohi
Proc. of the 14th International Symposium on High-Performance Computer Architecture (HPCA) (2008), pp. 264-275
On Hiding Multicore Complexity from System Software
Koushik Chakraborty
Gurindar S. Sohi
Workshop on Operating System Support for Heterogeneous Multicore Architectures (2007)
Hardware Support for Spin Management in Overcommitted Virtual Machines
Koushik Chakraborty
Gurindar S. Sohi
Proc. of the 15th International Conference on Parallel Architectures and Compilation Techniques (PACT) (2006), pp. 124-133
Computation Spreading: Employing Hardware Migration to Specialize CMP Cores On-the-fly
Koushik Chakraborty
Gurindar S. Sohi
Proc. of the 12th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS) (2006), pp. 283-292