Performance Measurement and Analysis

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Presentation transcript:

Performance Measurement and Analysis Chapter 11 Performance Measurement and Analysis

Chapter 11 Objectives Understand the ways in which computer performance is measured. Be able to describe common benchmarks and their limitations. Become familiar with factors that contribute to improvements in CPU and disk performance.

11.1 Introduction The ideas presented in this chapter will help you to understand various measurements of computer performance. You will be able to use these ideas when you are purchasing a large system, or trying to improve the performance of an existing system. We will discuss a number of factors that affect system performance, including some tips that you can use to improve the performance of programs.

11.2 The Basic Computer Performance Equation The basic computer performance equation has been useful in our discussions of RISC versus CISC: To achieve better performance, RISC machines reduce the number of cycles per instruction, and CISC machines reduce the number of instructions per program.

11.2 The Basic Computer Performance Equation We have also learned that CPU efficiency is not the sole factor in overall system performance. Memory and I/O performance are also important. Amdahl’s Law tells us that the system performance gain realized from the speedup of one component depends not only on the speedup of the component itself, but also on the fraction of work done by the component:

11.2 The Basic Computer Performance Equation In short, using Amdahl’s Law we know that we need to make the common case fast. So if our system is CPU bound, we want to make the CPU faster. A memory bound system calls for improvements in memory management. The performance of an I/O bound system will improve with an upgrade to the I/O system. Of course, fixing a performance problem in one part of the system can expose a weakness in another part of the system!

11.3 Mathematical Preliminaries Measures of system performance depend upon one’s point of view. A computer user is most often concerned with response time: How long does it take the system to carry out a task? System administrators are usually more concerned with throughput: How many concurrent tasks can the system handle before response time is adversely affected? These two ideas are related: If a system carries out a task in k seconds, then its throughput is 1/k of these tasks per second.

11.3 Mathematical Preliminaries In comparing the performance of two systems, we measure the time that it takes for each system to do the same amount of work. Specifically, if System A and System B run the same program, System A is n times as fast as System B if: System A is x% faster than System B if:

11.3 Mathematical Preliminaries Suppose we have two racecars that have just completed a 10 mile race. Car A finished in 3 minutes, and Car B finished in 4 minutes. Using our formulas, Car A is 1.25 times as fast as Car B, and Car A is also 25% faster than Car B:

11.3 Mathematical Preliminaries When we are evaluating system performance we are most interested in its expected performance under a given workload. We use statistical tools that are measures of central tendency. The one with which everyone is most familiar is the arithmetic mean (or average), given by:

11.3 Mathematical Preliminaries The arithmetic mean can be misleading if the data are skewed or scattered. Consider the execution times given in the table below. The performance differences are hidden by the simple average.

11.3 Mathematical Preliminaries If execution frequencies (expected workloads) are known, a weighted average can be revealing. The weighted average for System A is: 50  0.5 + 200  0.3 + 250  0.1 + 400  0.05 + 5000  0.05 = 380.

11.3 Mathematical Preliminaries However, workloads can change over time. A system optimized for one workload may perform poorly when the workload changes, as illustrated below.

11.3 Mathematical Preliminaries When comparing the relative performance of two or more systems, the geometric mean is the preferred measure of central tendency. It is the nth root of the product of n measurements. Unlike the arithmetic means, the geometric mean does not give us a real expectation of system performance. It serves only as a tool for comparison.

11.3 Mathematical Preliminaries The geometric mean is often uses normalized ratios between a system under test and a reference machine. We have performed the calculation in the table below.

11.3 Mathematical Preliminaries When another system is used for a reference machine, we get a different set of numbers.