A CPU executes , on average 60 machine instructions per μs. suppose that a program process a file of record where reading and writing a record from a file takes 10 μs each. if the program needs to execute 120 machine instructions between each read and write operation, what is the CPU utilization?
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When it comes to rating the performance of a processor, is calculating the Million Instructions Per Second (MIPS) a practical measure to use?
Or is finding the Execution Time (IC x CPI x 1/CR) the main thing to use?
Imagine you have one CPU that does 100 million tiny little instructions that don't do much on their own per second. Next; imagine you have another CPU where you need a quarter of the instructions to do the same work; which can do 50 million larger instructions per second. The second CPU has half as many MIPs but is twice as fast.
Now.. Imagine you have 2 CPUs that both execute the exact same instructions; where one CPU runs at 1 GHz, can do 5 instructions per cycle, and stalls rarely; and the other CPU runs at 4 GHz, can only do 2 instructions per cycle, and spends a lot more time stalled doing nothing (due to cache misses, branch mispredictions, etc). In this case the 1 GHz CPU might be significantly faster than the 4 GHz CPU.
Finally; imagine you have 2 CPUs that both execute the exact same instructions, both have exactly the same clock frequency, both execute the same number of instructions per cycle, and both spend exactly the same amount of time stalled. One CPU has overheats easily and had to "under-clock" itself to a crawl after 250 milliseconds of not being idle just to avoid melting itself, and the other CPU can go at max. speed continuously without ever overheating.
Execution time is how long it takes to do some work taking everything into account (and can be extremely different for different types of work); while MIPS is like a real estate agent determining how much a building is worth by measuring the weight of a rubber chicken.
For example, the data in the figure runtime.scanobject:
13.42s
runtime.scanobject 9.69s(4.51%) of 18.30s(8.52%).
5.33s
what is the meaning of the seconds and percent?
Thanks.
When CPU profiling is enabled, the Go program stops about 100 times per second and records a sample consisting of the program counters on the currently executing goroutine's stack.
That time and percentange is in reference to the sample.
Here is a nice reference for you to read more about it: https://blog.golang.org/profiling-go-programs
A certain computer system runs in a multi-programming environment using a non-preemptive
algorithm. In this system, two processes A and B are stored in the process queue,
and A has a higher priority than B. The table below shows estimated execution time for each
process; for example, process A uses CPU, I/O, and then CPU sequentially for 30, 60, and 30
milliseconds respectively. Which of the following is the estimated time in milliseconds
to complete both A and B? Here, the multi-processing overhead of OS is negligibly
small. In addition, both CPU and I/O operations can be executed concurrently, but I/O
operations for A and B cannot be performed in parallel.
UNIT : millisecond
CPU I/O CPU
A_______________30___________________60_________________30
B_______________45___________________45__________________--
Please help me.. i need to explain this in front of the class tomorrow but i cant seem get the idea of it...
A has the highest priority, but since the system is non-preemptive, this is only a tiebreaker when both processes need a resource at the same time.
At t=0, A gets the CPU for 30 ms, B waits as it needs the CPU.
At t=30, A releases the CPU, B gets the CPU for 45 ms, while A gets the I/O for 60 ms.
At t=75, the CPU sits idle as B is waiting for A to finish I/O, and A is not ready to use the CPU.
At t=90, A releases I/O and gets the CPU for another 30 ms, while B gets the I/O for 45 ms.
At t=120, A releases the CPU and is finished.
At t=135, B releases I/O and is finished.
It takes the longest path:
Non-preemptive multitasking or cooperative multitasking means that the process is kind of sharing a.e. the CPU time. In the worst case they use the worst time to achieve theire task.
CPU:
B = 45 is longer than A=30
45 +
I/O
A = 60 and B = 45
45 + 60
CPU again:
A = 30
45 + 60 + 30 = 135
i will explain in brief and please elaborate for your classroom discussion:
For your answer :135
when Process A waits for the I/O task,the CPU time will be given to Process B. so the complete time for process A and B would be
Process A (CPU )+ Process A I/O and Process B CPU + Process B I/O
30+60+45 = 135 ms
I am currently creating a program which identifies processes which are hung/out-of-control, and using an entire CPU core. The program then terminates them, so the CPU usage can be kept under control.
However, I have run into a problem: When I execute the 'tasklist' command on Windows, it outputs this:
Image Name: Blockland.exe
PID: 4880
Session Name: Console
Session#: 6
Mem Usage: 127,544 K
Status: Running
User Name: [removed]\[removed]
CPU Time: 0:00:22
Window Title: C:\HammerHost\Blockland\Blockland.exe
So I know that the line which says "CPU Time" is an indication of the total time, in seconds, used by the program ever since it started.
But let's suppose there are 4 CPU cores on the system. Does this mean that it used up 22 seconds of one core, and therefore used 5.5 seconds on the entire CPU in total? Or does this mean that the process used up 22 seconds on the entire CPU?
It's the total CPU time across all cores. So, if the task used 10 seconds on one core and then 15 seconds later on a different core it would report 25 seconds. If it used 5 seconds on all four cores simultaneously, it would report 20 seconds.
I have the following scenario:
machine 1: receives messages from outside and processes them (via a
Java application). For processing it relies on a database (on machine
2)
machine 2: an Oracle DB
As performance metrics I usually look at the value of processed messages per time.
Now, what puzzles me: none of the 2 machines is working on "full speed". If I look at typical parameters (CPU utilization, CPU load, I/O bandwidth, etc.) both machines look as they have not enough to do.
What I expect is that one machine, or one of the performance related parameters limits the overall processing speed. Since I cannot observe this I would expect a higher message processing rate.
Any ideas what might limit the overall performance? What is the bottleneck?
Here are some key values during workload:
Machine 1:
CPU load average: 0.75
CPU Utilization: System 12%, User 13%, Wait 5%
Disk throughput: 1 MB/s (write), almost no reads
average tps (as reported by iostat): 200
network: 500 kB/s in, 300 kB/s out, 1600 packets/s in, 1600 packets/s out
Machine 2:
CPU load average: 0.25
CPU Utilization: System 3%, User 15%, Wait 17%
Disk throughput: 4.5 MB/s (write), 3.5 MB/s (read)
average tps (as reported by iostat): 190 (very short peaks to 1000-1500)
network: 250 kB/s in, 800 kB/s out, 1100 packets/s in, 1100 packets/s out
So for me, all values seem not to be at any limit.
PS: for testing of course the message queue is always full, so that both machines have enough work to do.
To find bottlenecks you typically need to measure also INSIDE the application. That means profiling the java application code and possibly what happens inside Oracle.
The good news is that you have excluded at least some possible hardware bottlenecks.