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You will need to locate and utilize performance analysis tools to determine characteristics of your processor and process utilization / management on your Linux partition.
· How many CPUs are running?
· How fast is each CPU?
· What is the size of the cache on your CPU?
· What is meant by “User Time” in terms of CPU usage?
· What is meant by “Kernel” or “System” time in terms of CPU usage?
· What does it mean when a CPU is 90% idle? 0% idle?
· What is the difference between a running and runnable process? What is a blocked (also called “Uninteruptable”) thread or process?
Start your Linux Partition from a fresh boot and open the Terminal. Do not open any other applications at this time. Determine values for each of the following. Provide screenshots of command output.
What is the load average from the past 1, 5, and 15 minutes?
Which process appears to be using the most CPU on the system currently? How much is it using? Which process has used the most total amount of CPU time? How much total CPU time has been used?
For a 30 second time interval:
· How much CPU was used for tasks in “User Space?”
· How much CPU was used for tasks in “Kernel Space?”
· What percentage of time was the CPU idle?
· What percentage of time was the CPU “waiting?”
· Describe the activity on the run queue? i.e. runnable and blocked threads.
IMPORTANT: Before performing the tasks below, you will want to open at least one terminal window and maybe 2. You should be watching the performance statistics WHILE these applications are opening! This will yield the most valuable results in this lesson. i.e. Use top and vmstat to watch CPU statistics in real time as the system becomes busy.
Open as many applications as you can while still maintaining a Linux system that functions (the slower the system the better).
Now repeat all of the data gathering steps from above and record new values.
Document before and after results and create a summary documenting the changes you noticed (i.e. The effect of running applications on performance as verified through your performance analysis). Make a recommendation to add resources or change system parameters as necessary to increase performance under heavy loads. Be sure to use your data to back up your recommendation(s) if any.
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