Title: Designing User Interfaces Spring 1999
1SE 767-NT Software Performance Engineering Robert
Oshana Lecture 15 For more
information, please contact NTU Tape
Orders NTU Media Services (970) 495-6455
oshana_at_airmail.net
tapeorders_at_ntu.edu
2Where we are
- Introduction
- SPE Quick View
- SPE and the UML
- Software Execution Models
- Web applications and other distributed systems
- System execution models
- SPE data collection
- Software measurement and instrumentation
- Performance oriented design
- Performance patterns
- Performance anti-patterns
- Implementation solutions
- Web applications
- Embedded and real-time systems
- The SPE process
- Implementing SPE
3Resource estimation techniques
- Use measurements
- Study measurements
- Use a mentor
- Best-worst case estimates
- What to estimate
- Estimating I/O requirements
4More one estimating I/O requirements
- Need two types of information
- Number of physical I/Os
- I/O service times
- Two ways to estimate physical I/Os
- Estimate logical I/Os and sensitivity to hit
ratios and write ratios - Directly estimate which I/O requests are likely
to be found in or written from a buffer or a
cache and only count physical I/Os
5More one estimating I/O requirements
- A typical estimate
- Ip (i 1) X (1 h)
- Read requests that sequentially access a file,
number of physical I/Os is n/b - Some I/O devices read one track with each
physical I/O - Read request to a DB depend on complexity of SQL
statement - SELECT ltfieldsgt from table where keyx
6Estimating network messages
- Estimate the number of messages transferred or
the number of characters transferred - Account for headers as well as application
messages - Mi d / (m h)
- Mo (r x s) / (m h)
7Obtaining computer resource requirements
- Need computer resource requirements for each SW
resource requirement estimated - May be able to obtain estimates for computer
resource requirements from performance
specialists - Make sure to account for subtle overhead factors
- Unpacking a message before using
8Summary
- Need the following data for SPE
- Performance objectives
- Key performance scenarios
- Execution environment
- Software resource requirements
- Computer resource requirements
- Walkthroughs used to collect data
9Software measurement and instrumentation
10Where we are
- Introduction
- SPE Quick View
- SPE and the UML
- Software Execution Models
- Web applications and other distributed systems
- System execution models
- SPE data collection
- Software measurement and instrumentation
- Performance oriented design
- Performance patterns
- Performance anti-patterns
- Implementation solutions
- Web applications
- Embedded and real-time systems
- The SPE process
- Implementing SPE
11Introduction
- Measurement is a key part of the SPE process
- Data for SPE models
- Verify and validate models
- Determine whether performance goals have actually
been met - Monitor system performance over its lifetime
12Introduction
- Obtaining the right measurements is not easy
- Tools can help
- Also need a strategy
13What should you measure?
- System understanding
- Model specifications
- Model updates
- Model verification and validation
- Software performance evaluation
14Types of measurement data
- Workload data
- Data characteristics
- Execution characteristics
- Path characteristics
- Software resource usage
- Processing overhead
15Types of measurement data
- Computer system usage
- Scenario response time
- Scenario throughput
- Key computer system resource usage
- Resource utilization
- Resource throughput
- Resource queue lengths
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17Planning for performance measurement
- Key considerations
- Representative
- Reproducible
- Workload selection
- Load drivers
- Software
- Computer system environment
18Performance benchmarks
- Hardware or software system evaluations
- Volume testing
- Performance measurement
- SPEC
- EEMBC
- BDTI
19SE 767-NT Software Performance Engineering Robert
Oshana End of lecture For
more information, please contact NTU Tape
Orders NTU Media Services (970) 495-6455
oshana_at_airmail.net
tapeorders_at_ntu.edu