Understanding and Designing New Server Architectures for Emerging Warehouse-Computing Environments

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Citation: Kevin Lim, Parthasarathy Ranganathan, Jichuan Chang, Chandrakant D Patel, Trevor Nigel Mudge, Steven K. Reinhardt (2008/06) Understanding and Designing New Server Architectures for Emerging Warehouse-Computing Environments. International Symposium on Computer Architecture (RSS)
DOI (original publisher): 10.1145/1394608.1382148
Semantic Scholar (metadata): 10.1145/1394608.1382148
Sci-Hub (fulltext): 10.1145/1394608.1382148
Internet Archive Scholar (search for fulltext): Understanding and Designing New Server Architectures for Emerging Warehouse-Computing Environments
Download: https://dl.acm.org/doi/abs/10.1145/1394608.1382148
Tagged: Computer Science (RSS) computer architecture (RSS)

Summary

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Elsewhere

Problem

  • Internet companies are building huge datacenters.
  • Little academic prior work analyzes those workloads, including benchmarks.

Solution

  • Benchmark suite
    • Websearch
    • Webmail
      • Workload characteristics: interactive internet services
      • Application: SquirrelMail talking to courier-imap and exim, based on MS Exchange Server's "heavy usage" profile, and real size data from U Mich.
    • Ytube
      • Workload characteristics: rich media hosting
      • Application: SPECweb2005 with profile based on YouTube data.
      • Metric: Requests per second
    • MapReduce
      • Workload characteristics: analytics requests
      • Application: Word count and random writes
      • Metric: Latency
  • Models
    • Quantities: perf / $ (total cost of ownership assuming 3-year deprecation cycle), perf / W, perf / (infrastructure $), perf / (power & cooling $).
    • Performance model: Aggregated from individual node performance
    • Cost model: Hardware cost + power & cooling cost
      • . See paper for details.
      • Sources: publicly available prices, private correspondance
  • Questions:
    • Can using low-end processor help?
      • HPC uses high-end "fat" nodes; if switch to "dumb" nodes, one could have more for the same price.
      • Result: Depends on the benchmark. Yes if memory- or IO-bound.
    • Can changing the cooling system help?
      • Yes
    • Can shared memory help?
      • It's too hard to give each node enough memory for the worst-case working set; instead, they should pool their resources hierarchically. Probably each node won't have the worst-case at the same time, so one node can use another's vacant memory.
      • Two-level memory hierarchy with first-level sized to 25% of the baseline memory seems to work well.
      • Kind of. More gains possible in the future.
    • Can using low-end hard-drive help?
      • Only if their prices drops in the future.

Discussion

  • Further research needed to determine applicability of benchmark suite.
  • More work is needed to validate performance model
  • They use Amdahl's law as a simplifying assumption.
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