I am trying to get the CPU usage by specific process
Like in the below image the CPU column shows the CPU usage by specific process
But did not get similar counter in perfmon
I tried using \Process\% Processor Time but the value shown in PerfMon are different.
Thanks in Advance
Solved from Below Post:
Didn't find any direct way from perfmon so decided to write code for that and it worked.
Calculating process cpu usage from Process.TotalProcessorTime
From the perfmon snapshot, there are two counters and the graphs of both counters have the same color. That's why the result is confusing. You should either uncheck the first counter (which represents the total processor time) or change the color of one of the counters by right clicking on the counter and accessing its properties.
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I have recently started coding in verilog. I have completed my first project, prototyping a MIPS 32 processor using 5 stage pipelining. Now my next task is to implement a single level cache hiearchy on the instruction set memory.
I have sucessfully implemented a 2-way set associative cache.
Previously I had declared the instruction set memory as a array of registers, so whenever I need to access the next instruction in IF stage, the data(instruction) gets instantaneously allotted to the register for further decoding (since blocking/non_blocking assignment is instantaneous from any memory location).
But now since I have a single level cache added on top of it, it takes a few more cycles for the cache FSM to work (like data searching, and replacement policies in case of cache miss). Max. delay is about 5 cycles when there is a cache miss.
Since my pipelined stage proceeds to the next stage within just a single cycle, hence whenever there is a cache miss, the cache fails to deliver the instruction before the pipeline stage moves to the next stage. So desired output is always wrong.
To counteract this , I have increased the clock of the cache by 5 times as compared the processor pipelined clock. This does do the work, since the cache clock is much faster, it need not to worry about the processor clock.
But is this workaround legit?? I mean i haven't heard of multiple clocks in a processor system. How does the processors in real world overcome this issue.
Yes ofc, there is an another way of using stall cycles in pipeline until the data is readily made available in cache (hit). But just wondering is making memory system more faster by increasing clock is justified??
P.S. I am newbie to computer architecture and verilog. I dont know about VLSI much. This is my first question ever, because whatever questions strikes, i get it readily available in webpages, but i cant find much details about this problem, so i am here.
I also asked my professor, she replied me to research more in this topic, bcs none of my colleague/ senior worked much on pipelined processors.
But is this workaround legit??
No, it isn't :P You're not only increasing the cache clock, but also apparently the memory clock. And if you can run your cache 5x faster and still make the timing constraints, that means you should clock your whole CPU 5x faster if you're aiming for max performance.
A classic 5-stage RISC pipeline assumes and is designed around single-cycle latency for cache hits (and simultaneous data and instruction cache access), but stalls on cache misses. (Data load/store address calculation happens in EX, and cache access in MEM, which is why that stage exists)
A stall is logically equivalent to inserting a NOP, so you can do that on cache miss. The program counter needs to not increment, but otherwise it should be a pretty local change.
If you had hardware performance counters, you'd maybe want to distinguish between real instructions vs. fake stall NOPs so you could count real instructions executed.
You'll need to implement pipeline interlocks for other stages that stall to wait for their inputs to be ready, e.g. a cache-miss load followed by an add that uses the result.
MIPS I had load-delay slots (you can't use the result of a load in the following instruction, because the MEM stage is after EX). So that ISA rule hides the 1 cycle latency of a cache hit without requiring the HW to detect the dependency and stall for it.
But a cache miss still had to be detected. Probably it stalled the whole pipeline whether there was a dependency or not. (Again, like inserting a NOP for the rest of the pipeline while holding on to the incoming instruction. Except this isn't the first stage, so it has to signal to the previous stage that it's stalling.)
Later versions of MIPS removed the load delay slot to avoid bloating code with NOPs when compilers couldn't fill the slot. Simple HW then had to detect the dependency and stall if needed, but smarter hardware probably tracked loads anyway so they could do hit under miss and so on. Not stalling the pipeline until an instruction actually tried to read a load result that wasn't ready.
MIPS = "Microprocessor without Interlocked Pipeline Stages" (i.e. no data-hazard detection). But it still had to stall for cache misses.
An alternate expansion for the acronym (which still fits MIPS II where the load delay slot as removed, requiring HW interlocks to detect that data hazard) would be "Minimally Interlocked Pipeline Stages" but apparently I made that up in my head, thanks #PaulClayton for catching that.
Is there an easy way to increase the RAM available in Knime through a config file or through menu options?
I am constantly running into "heap-space" errors during execution and it by default limits the number of categorical variables to 1,000, as well as difficulty displaying charts with more than n values (~10,000).
Example error:
ERROR Decision Tree Learner 0:65 Execute failed: Java heap space
Thanks!
Sure, you can edit knime.ini (in the knime or knime_<version> folder) and change the row starting with -Xmx (I think by default it is 2048m, two GiB). Though do not use so much memory that would cause the OS to swap as Java do not play very well with swapping.
(Displaying too many variables might still be slow, maybe you could aggregate them somehow.)
I'm having a bit of problems understanding how or if its possible to share a work load between a gpu and cpu. I have a large log file that I need to read each line then run about 5 million operations on(testing for various scenarios). My current approach has been to read a few hundred lines, add it to an array and then send it to each GPU, which is working fine but because there is so much work per line and so many lines it takes a long time. I noticed that while this is going on my CPU cores are basically doing nothing. I'm using EC2, so I have 2 quad core Xeon & 2 Tesla GPUs, one cpu core reads the file(running the main program) and the GPU's do the work so I'm wondering how or what can I do to involve the other 7 cores into the process?
I'm a bit confused at how to design a program to balance the tasks between GPU/CPU because they both would finish the jobs at different times so I couldn't just send it to them all at the same time. I thought about setting up a queue(I'm new to c, so not sure if this is possible yet) but then is there a way to know when a GPU job is completed(since I thought sending jobs to Cuda was asynchronous)? I kernel is very similar to a normal c function so converting it for cpu usage is not problem just balancing the work seems to be the issue. I went though 'Cuda by example' again but couldn't really find anything referring to this type of balancing.
Any suggestions would be great.
I think the key is to create a multithreaded app, following all the common practices for that, and have two types of worker threads. One that does work with the GPU and one that does work with the CPU. So basically, you will need a thread pool and a queue.
http://en.wikipedia.org/wiki/Thread_pool_pattern
The queue can be very simple. You can have one shared integer that is the index of the current row in the log file. When a thread is ready to retrieve more work, it locks that index, gets some number of lines from the log file, starting at the line designated by the index, then increases the index by the number of lines that it retrieved, and then unlocks.
When a worker thread is done with one chunk of the log file, it posts its results back to the main thread and gets another chunk (or exits if there are no more lines to process).
The app launches some combination of GPU and CPU worker threads to utilize all available GPUs and CPU cores.
One problem you may run into is that if the CPU is busy, performance of the GPUs may suffer, as slight delays in submitting new work or processing results from the GPUs are introduced. You may need to experiment with the number of threads and their affinity. For instance, you may need to reserve one CPU core for each GPU by manipulating thread affinities.
Since you say line-by-line may be you can split the jobs across 2 different process -
One CPU + GPU Process
One CPU process that utilized remaining 7 cores
You can start of each process with different offsets - like 1st process reads the lines 1-50, 101-150 etc while the 2nd one reads 51-100, 151-200 etc
This will avoid you the headache of optimizing CPU-GPU interaction
I have a custom python script that monitors the call logs from a Nortel phone system. This phone system is under extremely high volume throughout the day and it's starting to appear that some records may be getting lost.
Some of you may dislike this, but I'm not interested in sharing the source code or current method in any way. I would rather consider this from a "new project" approach.
I'm looking for insight into the easiest and safest way to reliably monitor heavy data output through a serial port on Linux. I'm not limiting this to any particular set of tools or languages, I want to find out what works best to do this one critical job. I'm comfortable enough parsing the data and inserting it into mysql that we could just assume the data could be dropped to a text file.
Thank you
Well, the way that I would approach this this to have 2 threads (or processes) working.
Thread 1: The read thread
This thread does nothing but read data from the raw serial port and put the data into a local buffer/queue (In memory is preferred for speed). It should do nothing else. Depending on the clock speed of the serial connection, this should be pretty easy to do.
Thread2: The processing thread
This thread just sleeps until there is data in the local buffer to process, then reads and processes it. That's it.
The reason for splitting it apart in two, is so that if one is busy (a block in MySQL for the processing thread) it won't affect the other. After all, while the serial port is buffered by the OS, the buffer size is limited.
But then again, any local program is likely going to be way faster than the serial port can send data. Serial transfer is actually quite slow relative to the clock speed of the processor (115.2kbps is about the limit on standard hardware). So unless you're CPU speed bound (such as on an Arduino), I can't see normal conditions affecting it too much. So your choice of language really shouldn't be of too much concern (assuming modern hardware). Stick to what you know.
How to measure current load of MySQL server? I know I can measure different things like CPU usage, RAM usage, disk IO etc but is there a generic load measure for example the server is at 40% load etc?
mysql> SHOW GLOBAL STATUS;
Found here.
The notion of "40% load" is not really well-defined. Your particular application may react differently to constraints on different resources. Applications will typically be bound by one of three factors: available (physical) memory, available CPU time, and disk IO.
On Linux (or possibly other *NIX) systems, you can get a snapshot of these with vmstat, or iostat (which provides more detail on disk IO).
However, to connect these to "40% load", you need to understand your database's performance characteristics under typical load. The best way to do this is to test with typical queries under varying amounts of load, until you observe response times increasing dramatically (this will mean you've hit a bottleneck in memory, CPU, or disk). This load should be considered your critical level, which you do not want to exceed.
is there a generic load measure for example the server is at 40% load ?
Yes! there is:
SELECT LOAD_FILE("/proc/loadavg")
Works on a linux machine. It displays the system load averages for the past 1, 5, and 15 minutes.
System load averages is the average number of processes that are either in a runnable or uninterruptable state. A process in a runnable state is either using the CPU or waiting to use the CPU.
A process in uninterruptable state is waiting for some I/O access, eg waiting for disk. The averages are taken over the three time intervals. Load averages are not normalized for the number of
CPUs in a system, so a load average of 1 means a single CPU system is loaded all the time while on a 4 CPU system it means it was idle 75% of the time.
So if you want to normalize you need to count de number of cpu's also.
you can do that too with
SELECT LOAD_FILE("/proc/cpuinfo")
see also 'man proc'
with top or htop you can follow the usage in Linux realtime
On linux based systems the standard check is usually uptime, a load index is returned according to metrics described here.
aside from all the good answers on this page (SHOW GLOBAL STATUS, VMSTAT, TOP...) there is also a very simple to use tool written by Jeremy Zawodny, it is perfect for non-admin users. It is called "mytop". more info # http://jeremy.zawodny.com/mysql/mytop/
Hi friend as per my research we have some command like
MYTOP: open source program written using PERL language
MTOP: also an open source program written on PERL, It works same as MYTOP but it monitors the queries which are taking longer time and kills them after specific time.
Link for details of above command