Deep sampling

Deep sampling is a variation of statistical sampling in which precision is sacrificed for insight. Small numbers of samples are taken, with each sample containing much information. The samples are taken approximately uniformly over the resource of interest, such as time or space. It is useful for identifying large hidden problems.

Examples:

See also

References

  • Dunlavey, “Performance tuning with instruction-level cost derived from call-stack sampling”, ACM SIGPLAN Notices 42, 8 (August, 2007), pp. 4–8.
  • Dunlavey, “Performance Tuning: Slugging It Out!”, Dr. Dobb's Journal, Vol 18, #12, November 1993, pp 18–26.