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Algorithm analysis and efficiency

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This document discusses algorithm analysis and efficiency. It defines an algorithm as a step-by-step set of instructions to solve a problem with a definite end point. Algorithm analysis is important to establish if a given algorithm uses reasonable resources. Algorithm efficiency relates to the amount of computational resources used, and the goal is to minimize usage. The main measures of efficiency are time complexity, or how long an algorithm takes, and space complexity, or how much memory is needed. Less common measures include transmission size, external risk, response time, and total cost of ownership.

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ALGORITHM ANALYSIS AND EFFICIENCY
WHAT IS ALGORITHM?  Algorithm is a step by step instruction to solve a given problem.  An Algorithm must have definite end point so that when the input has been processed and the desired output achieved,the process stops.  Example:To add two numbers Accept two numbers as num1 and num2 Find the sum of two numbers PRINT SUM
Algorithm analysis and efficiency
WHY ALGORITHM ANALYSIS?  A problem can have solution/multiple solutions.  To establish if a given algorithm uses a reasonable amount of resources to solve a problem,an analysis of algorithm is required.
ALGORITHM EFFICIENCY  Algorithmic efficiency are properties of algorithm which relate to amount of computational resources used by an algorithm.  For maximum efficiency,we wish to minimise resource usage.
MEASURES OF ALGORITHM EFFICIENCY  Time Complexity(how long does algorithm take to complete)  Space complexity(how much working memory is needed by algorithm) This has two aspects 1.Amount of memory needed by the code 2.Amount of memory needed for data on which the code operates.
There are also less common measures.They are  Transmission size :Bandwidth could be a limiting factor.Data compression can be used to reduce amount of data to be transmitted.  External risk :Space needed on a disk.  Response Time :Particularly in realtime applications when computer system must respond quickly to some external extent.  Total cost of Ownership:Particularly if computer is dedicated to one particular algorithm.
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Algorithm analysis and efficiency

  • 2. WHAT IS ALGORITHM?  Algorithm is a step by step instruction to solve a given problem.  An Algorithm must have definite end point so that when the input has been processed and the desired output achieved,the process stops.  Example:To add two numbers Accept two numbers as num1 and num2 Find the sum of two numbers PRINT SUM
  • 4. WHY ALGORITHM ANALYSIS?  A problem can have solution/multiple solutions.  To establish if a given algorithm uses a reasonable amount of resources to solve a problem,an analysis of algorithm is required.
  • 5. ALGORITHM EFFICIENCY  Algorithmic efficiency are properties of algorithm which relate to amount of computational resources used by an algorithm.  For maximum efficiency,we wish to minimise resource usage.
  • 6. MEASURES OF ALGORITHM EFFICIENCY  Time Complexity(how long does algorithm take to complete)  Space complexity(how much working memory is needed by algorithm) This has two aspects 1.Amount of memory needed by the code 2.Amount of memory needed for data on which the code operates.
  • 7. There are also less common measures.They are  Transmission size :Bandwidth could be a limiting factor.Data compression can be used to reduce amount of data to be transmitted.  External risk :Space needed on a disk.  Response Time :Particularly in realtime applications when computer system must respond quickly to some external extent.  Total cost of Ownership:Particularly if computer is dedicated to one particular algorithm.