HPCA07-TUTORIAL

‰‰‰„„„‰‰‰‰„„„‰„„„„„„„‰‰„„‰‰„„„‰‰‰Computer Performance ModelingGoal: Estimating and understanding the performance of computer systemsPractical Cache Performance Low-Level ModelsModeling for Computer ArchitectsVarious levels of details: functional, trace, cycle-accurate, etc.ProsVersatile: adaptable to new architectures and workloadDetails: can embed very detailed statistics Yan Solihin, NCSU, solihin@ncsu.eduPopular: SimpleScalar, SIMICS widely usedFei Guo, NCSU, fguo@ncsu.eduConsThomas Puzak, IBM, trpuzak@us.ibm.comO(n) overhead, scales with workload size: each instruction/event is simulated to capture its effectPhil Emma, IBM, pemma@us.ibm.comSlow: realistic workload has many billions of instructions2Modeling MethodsComputer Performance ModelingHigh-Level Models White Box Purpose: Evaluating gross trade-offs of designsModel incorporates knowledge about the system (e.g. relationships of parameters are known a priori)ProsAnalytical or heuristics-basedShort execution time, and sometimes O(1)Requires little coding Pros: models reveal insights &explain “why”, no training requiredReveal basic relationships of variablesMay reveal non-obvious trends and insightsCons: problem-specific solutionConsBlack BoxLess versatileModel learns knowledge about the systemRequires performance modeling expertise AI-based: neural networks, decision tree, curve fitting, etc.Uses: Pros: can model complex problem ...