I have a computation-intensive application, which needs to run on a Windows server with no other applications on it. The application is designed for horizontal scalability so that it can run on multiple servers if the input load is more. Should I be worried about the CPU usage and ensure that every time it goes over a certain threshold, I should bring in a new server and get the application running on it to spread the load? Or is it ok if the app runs continuously at 100% CPU load?
Basically are there any disadvantages of letting an app run at 100%?
I understand overheating of the CPU could be an issue.
Also context switching between threads of the application could cause the overall thorughput to be reduced.
Any other? Is there any guideline regarding a threshold to be set for CPU utilization?
Thanks,
Yash
Intel (i) series i5 and i7 allow hyper-threading and turbo-boosting which makes the CPU run at 105-110% from my knowledge.
Overheating will be a problem but if you can set affinities for different cores on different times if you have a quad core 2 can run on turbo-boost while the other two cool down. Assuming you can do that.
I hope I answered your question (in a way).
Related
I'm a researcher in statistical pattern recognition, and I often run simulations that run for many days. I'm running Ubuntu 12.04 with Linux 3.2.0-24-generic, which, as I understand, supports multicore and hyper-threading. With my Intel Core i7 Sandy Bridge Quadcore with HTT, I often run 4 simulations (programs that take a long time) at the same time. Before I ask my question, here are the things that I already (think I) know.
My OS (Ubuntu 12.04) detects 8 CPUs due to hyper-threading.
The scheduler in my OS is clever enough never to schedule two programs to run on two logical (virtual) cores belonging to the same physical core, because the OS supports SMP (Simultaneous Multi-Threading).
I have read the Wikipedia page on Hyper-Threading.
I have read the HowStuffWorks page on Sandy Bridge.
OK, my question is as follows. When I run 4 simulations (programs) on my computer at the same time, they each run on a separate physical core. However, due to hyper-threading, each physical core is split into two logical cores. Therefore, is it true that each of the physical cores is only using half of its full capacity to run each of my simulations?
Thank you very much in advance. If any part of my question is not clear, please let me know.
This answer is probably late, but I see that nobody offered an accurate description of what's going on under the hood.
To answer your question, no, one thread will not use half a core.
One thread can work inside the core at a time, but that one thread can saturate the whole core processing power.
Assume thread 1 and thread 2 belong to core #0. Thread 1 can saturate the whole core's processing power, while thread 2 waits for the other thread to end its execution. It's a serialized execution, not parallel.
At a glance, it looks like that extra thread is useless. I mean the core can process 1 thread at once right?
Correct, but there are situations in which the cores are actually idling because of 2 important factors:
cache miss
branch misprediction
Cache miss
When it receives a task, the CPU searches inside its own cache for the memory addresses it needs to work with. In many scenarios the memory data is so scattered that it is physically impossible to keep all the required address ranges inside the cache (since the cache does have a limited capacity).
When the CPU doesn't find what it needs inside the cache, it has to access the RAM. The RAM itself is fast, but it pales compared to the CPU's on-die cache. The RAM's latency is the main issue here.
While the RAM is being accessed, the core is stalled. It's not doing anything. This is not noticeable because all these components work at a ridiculous speed anyway and you wouldn't notice it through some CPU load software, but it stacks additively. One cache miss after another and another hampers the overall performance quite noticeably.
This is where the second thread comes into play. While the core is stalled waiting for data, the second thread moves in to keep the core busy. Thus, you mostly negate the performance impact of core stalls.
I say mostly because the second thread can also stall the core if another cache miss happens, but the likelihood of 2 threads missing the cache in a row instead of 1 thread is much lower.
Branch misprediction
Branch prediction is when you have a code path with more than one possible result. The most basic branching code would be an if statement.
Modern CPUs have branch prediction algorithms embedded into their microcode which try to predict the execution path of a piece of code. These predictors are actually quite sophisticated and although I don't have solid data on prediction rate, I do recall reading some articles a while back stating that Intel's Sandy Bridge architecture has an average successful branch prediction rate of over 90%.
When the CPU hits a piece of branching code, it practically chooses one path (path which the predictor thinks is the right one) and executes it. Meanwhile, another part of the core evaluates the branching expression to see if the branch predictor was indeed right or not. This is called speculative execution.
This works similarly to 2 different threads: one evaluates the expression, and the other executes one of the possible paths in advance.
From here we have 2 possible scenarios:
The predictor was correct. Execution continues normally from the speculative branch which was already being executed while the code path was being decided upon.
The predictor was wrong. The entire pipeline which was processing the wrong branch has to be flushed and start over from the correct branch.
OR, the readily available thread can come in and simply execute while the mess caused by the misprediction is resolved. This is the second use of hyperthreading.
Branch prediction on average speeds up execution considerably since it has a very high rate of success. But performance does incur quite a penalty when the prediction is wrong.
Branch prediction is not a major factor of performance degradation since, like I said, the correct prediction rate is quite high.
But cache misses are a problem and will continue to be a problem in certain scenarios.
From my experience hyperthreading does help out quite a bit with 3D rendering (which I do as a hobby). I've noticed improvements of 20-30% depending on the size of the scenes and materials/textures required. Huge scenes use huge amounts of RAM making cache misses far more likely. Hyperthreading helps a lot in overcoming these misses.
Since you are running on a Linux kernel you are in luck because the scheduler is smart enough to make sure your tasks is divided on between your physical cores.
Linux became hyperthredding aware in kernel 2.4.17 ( ref: http://kerneltrap.org/node/391 )
Note that the reference is from the old O(1) scheduler. Linux now uses the CFS scheduling algorithm which was introduced in kernel 2.6.23 and should be even better.
But as already suggested you can experiment by disabling hyper threading in bios and see if your particular workload runs faster or slower with or without hyperthreading enabled. If you start 8 tasks instead of 4 you will probably find that the total executing time for 8 tasks on hyperthreading is faster than two separate runs with 4 tasks but again the best thing to do is to experiment. Good luck!
If you are really want just 4 dedicated cores, you should be able to disable hyperthreading in your BIOS page. Also, and this part I'm less clear on, I believe that the processor is smart enough to do more work on a single thread if its second logical core is idle.
No, it's not exactly true. A hyperthreaded core is not two cores. Some things can run in parallel, but not as much as on two separate cores.
The problem is with Memory management because I keep receiving “Out of Memory exception”.
Here are the scenarios where we face the problem:
Please note:
1. The site/application is developed in ASP.Net and uploaded on a server with the following specs:
- Windows Server 2008 (R2) Standard
- Intel Xeon L5520#2.27GHz 2.27GHz
- RAM = 8GB
- System Type = 64bit
The application is event management based web application where the requirements include saving huge amount of data in Sessions etc (mentioning this in case it is relevant)
The applications/site works fine until we:
Edit a file directly on the server
Update a file from repository
Copy/Paste a file (we don’t usually edit code using this technique)
Please note, all of the above hold true ONLY when the traffic to the site is high that is,
The issue/error “Out of Memory” is not produced when the traffic/visits is low
Details of:
System Properties > Advanced > Performance Settings > Advanced tab
Total paging file size for all drives: 16362 MB
In web.config
Is there any way we can debug this problem to the core and find out a solution. Can you please provide links/help where we can further investigate this problem?
Best regards,
Farrukh
Out of Memory Exceptions are common with applications that see periodic transaction surges while keeping larger volumes of data in memory. This problem does, however, depend on your application and architecture. Below are a few pointers:
Hardware - you have Xeon 5500 (Intel Nehalem chips). These are very good at handling memory. You should be good here.
OS - Windows Server 2008 R2 - As an OS this system will handle more than enough memory for you (you are good here, see link for capabilities: Memory Limits for Windows)
Physical Memory - Did you say you have 8 GB on the server? Note you app is allowing 16 GB. There is one issue. If your app requests more memory than physically available you will see your error. But this is not your only concern ...
CLR / GC limitations - Your application has a "paging file size" of 16+ GB. This is probably your issue.
GC is the heart of your problem for you. In terms of why, it is the same reason Java and the JVM have issues whenever an application exceeds 2-4 GB. That requires a look at the actual process of GC.
You have "old generation" and "young generation" Garbage Collection processes. As you app runs the CLR tries to keep your memory space organized. These processes force all threads to pause (phase changes) when GC mark and swap processes occur. The problem here is, depending on how your code is written and the amount of memory you keep around for long periods, you can run into memory issues.
Any time you press a runtime environment to exceed the 4 GB threshold you will see exponential increases in collection times. When you hit the "stop the world" pause (the old gen GC where everything gets cleaned up) the CLR has to go through the entire heap and de-allocate memory. Based on your app, 16 GB may give you issues even with more physical memory (Windows Server 2008 R2 - Enterprise or DataCenter can support 2 TB). Even if you feed it more physical memory you may see LONG collection times when your full GC hits.
Ideally I would do the following:
Get more physical memory (you never want to come withing 600MB of your total physical memory allocated to your application to avoid out of memory errors, but your buffer does depend on your load and the application's ability to handle it ... you may want a larger safety net to be safe).
Once you have the physical memory you need run GC logs while stressing the app. This will give you an idea where you see exponential degradation in performance and what level your app can support when considering Heap size (Memory). You may want to find a way to get your 16GB page down to a smaller size. I do know with .Net 4.0 Microsoft has made some solid improvements to the GC process, including allowing a background thread to maintain GC. This should give you the ability to support larger heaps (in theory) ... but nothing beats real tests on the app. Check out this link for more info:
Garbage Collection Performance (Asp.net 4.0) - Also, as I am limited on links. Navigate to the Fundamentals page for some great explanations on new GC features of ASP.Net 4.0
(http://msdn.microsoft.com/en-us/library/ee787088.aspx#concurrent_garbage_collection)
Hope this helps!
PS - Anyone out there on lesser hardware will need to be aware of the ASP.NET use of the GC thread. If you are running something in development like a Core Duo you have to consider that 50% of your compute power will go to GC optimization. This means that Hardware (number of cores) is important to consider. If you have more than you need this process should theoretically help performance. If you are constrained on cores either get better hardware or use an older version of ASP.Net or consider turning the feature off (if possible). Second, if latency is a concern, using "hyper-threading" does have an impact on performance as well. You always get better performance on "physical" cores ... but that will not be a concern for 99.9% of the applications out there.
2 GB by default. If the application is large address space aware (linked with /LARGEADDRESSAWARE), it gets 4 GB (see http://msdn.microsoft.com/en-us/library/aa366778.aspx)
They're still limited to 2 GB since many application depends on the top bit of pointers to be zero.
My Asp.net application uses
25-30% of the CPU on a test server which has 600 MB Ram on it.
I can see the asp_wb process taking that much percentage of CPU.
This is when I am testing using one user.
How many users can the server afford then without falling over?
Is there a relationship between the CPU Usage and number of user aka if there are 2 users my application will sky rocket to 60% of memory usage?
Or does/Should/How does the server handle this?
The asp.net is base on pools and not on users.
Some memory per user is going on user session, but I believe that you not hold huge amount of data on sessions (did you ?).
Now I suggest ti run process explorer from sysinternals, and check on w3wp.exe the working set and the virtual size of the memory for this. You can do that by open this 2 columns on Process Memory tab.
Then you see there how many memory asp.net needs for your application.
Second step if to check how you have configure your pool by open it. Maybe you have configure it to recycle too often, or to recycle when you have more than 125k working set memory, and your program have 200k working set memory. So you need to recalibrate some values.
Together with process explorer you can see how much memory your application need, and setup correctly the pool.
Of cource maybe there are other problems and other issues with the memory but asp.net is not eat memory for every user and you need to check where your memory is used - and the process explorer is a good tool for this job.
Hope this help.
I want to use the highest possible number of threads (to use less computers) but without making the bottleneck to be in the client.
JMeter can simulate a very High Load provided you use it right.
Don't listen to Urban Legends that say JMeter cannot handle high load.
Now as for answer, it depends on:
your machine power
your jvm 32 bits or 64 bits
your jvm allocated memory -Xmx
your test plan ( lot of beanshell, post processor, xpath ... Means lots of cpu)
your os configuration (tunable)
Gui / non gui mode
So there is no theorical answer but following Best Practices will ensure JMeter performs well.
Note that with jmeter you can distribute load through remote testing, read:
Remote Testing > 15.4 Using a different sample sender
And finally use cloud based testing if it's not enough.
Read this for tuning tips:
http://www.ubik-ingenierie.com/blog/jmeter_performance_tuning_tips/
Read this book for doing load testing and using JMeter correctly.
I have used JMeter a fair bit and found it is not great at generating really high load. On a 2Ghz Core2 Duo with 2Gb memory you can reasonably expect about 100 threads.
That being said, it is best to run it on your hardware so that the CPU of the PC does not peak at 100% - a stable 80%-90% is best otherwise the results are affected.
I have also tried WAPT 5 - it successfully ran 1000+ threads from the same PC. It is not free but it is more useable than JMeter but doesn't have all of the features.
Outdated answer since at least version 2.6 see https://stackoverflow.com/a/11922239/460802 for a more up to date one.
The JMeter Wiki reports cases where JMeter was used with as much as 1000 threads. I have used it with at most 100 threads, but the Links in the Wiki suggest resource reductions I never tried.
One of the issues we had with running JMeter on Windows XP was the Windows XP TCP Connection Limit. Limit should be removed in order to run use the JMeter to workstation’s full potential
More info here. AFAIK, does not apply to other OS.
I used JMeter since 2004 and i launched lot of load tests.
With PC Windows 7 64 bits 4Go RAM iCore5.
I think JMeter can support 300 to 400 concurrent threads for Http (Sampler) protocol with only one "Aggregate Report Listener" who writes in the log file results and timers between call pages.
For a big load test you could configure JMeter with slaves (load generators) like this
http://jmeter-plugins.org/wiki/HttpSimpleTableServer/
I have already done tests with 11 PC slaves to simulate 5000 threads.
I have not used JMeter, but the answer probably depends on your hardware. Best bet might be to establish metrics of performance, guess at the number of threads and then run a binary search as follows.
Source was Wikipedia.
Number guessing game...
This rather simple game begins something like "I'm thinking of an integer between forty and sixty inclusive, and to your guesses I'll respond 'High', 'Low', or 'Yes!' as might be the case." Supposing that N is the number of possible values (here, twenty-one as "inclusive" was stated), then at most questions are required to determine the number, since each question halves the search space. Note that one less question (iteration) is required than for the general algorithm, since the number is already constrained to be within a particular range.
Even if the number we're guessing can be arbitrarily large, in which case there is no upper bound N, we can still find the number in at most steps (where k is the (unknown) selected number) by first finding an upper bound by repeated doubling. For example, if the number were 11, we could use the following sequence of guesses to find it: 1, 2, 4, 8, 16, 12, 10, 11
One could also extend the technique to include negative numbers; for example the following guesses could be used to find −13: 0, −1, −2, −4, −8, −16, −12, −14, −13
It is more dependent on the kind of performance testing you do(load, spike, endurance etc) on a specific server (a little on hardware dependency)
Keep in mind around these parameters
- the client machine on which you are targeting the run of jmeter, there will be a certain amount of heap memory allocated, ensure to have a healthy allocation so that the script does not error out. The highest i had run on jmeter was 1500 on a local environment ( client - server arch), On a Web arch, the highest i had a run was based upon Non- functional requirement were limited to 250 threads,
so it ideally depends on the kinds of performance testing and deployment style and so on..
There is not standard number for this. The maximum number of threads that you can generate from one computer depends completely on the computer's hardware and the OS. The OS by default occupies certain amount of CPU and the RAM.
To find out the maximum threads your computer can handle you can prepare a sample test and run it with only a few threads. Then with each cycle of test run increase the number of threads gradually. During this you also need to monitor the CPU, RAM, Disk I/O and Network I/O of your computer. The moment any of these reach near or beyond 80% (Again for you to decide if near is okay for you or beyond), that is the maximum number of threads your computer can handle. To be on the safer side I would stop at the number when the resource utilization reaches 70%.
It'll depend on the hardware you run on as well as the underlying script. I've always felt that this fuzziness is the biggest problem with traditional load testing tools. If you've got a small budget ($200 or so gets you a LOT of testing), check out my company's load testing service, BrowserMob.
Besides our Real Browser Users (RBUs) which control thousands on actual browsers for the purpose of performance and load testing, we also have traditional virtual users (VUs). Scripts are written in JavaScript and can make various HTTP calls.
The reason I bring it up is that I always felt that the game of trying to figure out how many VUs you can fit on your load gen hardware is dangerous. It's so easy to get bad results without realizing it.
To solve that for BrowserMob, we took an extremely conservative approach on the number of VUs and RBUs per CPU core: no more than 1 browser or 50 threads per CPU core, and sometimes much less. In the world of cloud computing, CPU cycles are so cheap that it just doesn't make sense to try to overload machines.
How much traffic can one web server handle? What's the best way to see if we're beyond that?
I have an ASP.Net application that has a couple hundred users. Aspects of it are fairly processor intensive, but thus far we have done fine with only one server to run both SqlServer and the site. It's running Windows Server 2003, 3.4 GHz with 3.5 GB of RAM.
But lately I've started to notice slows at various times, and I was wondering what's the best way to determine if the server is overloaded by the usage of the application or if I need to do something to fix the application (I don't really want to spend a lot of time hunting down little optimizations if I'm just expecting too much from the box).
What you need is some info on Capacity Planning..
Capacity planning is the process of planning for growth and forecasting peak usage periods in order to meet system and application capacity requirements. It involves extensive performance testing to establish the application's resource utilization and transaction throughput under load. First, you measure the number of visitors the site currently receives and how much demand each user places on the server, and then you calculate the computing resources (CPU, RAM, disk space, and network bandwidth) that are necessary to support current and future usage levels.
If you have access to some profiling tools (such as those in the Team Suite edition of Visual Studio) you can try to set up a testing server and running some synthetic requests against it and see if there's any specific part of the code taking unreasonably long to run.
You should probably check some graphs of CPU and memory usage over time before doing this, to see if it can even be that. (A number alike to the UNIX "load average" could be a useful metric, I don't know if Windows has anything like it. Basically the average number of threads that want CPU time for every time-slice.)
Also check the obvious, that you aren't running out of bandwidth.
Measure, measure, measure. Rico Mariani always says this, and he's right.
Measure req/sec, RAM, CPU, Sessions, etc.
You may come up with a caching strategy (Output caching, data caching, caching dependencies, and so on.)
See also how your SQL Server is doing... indexes are a good place to start but not the only thing to look at..
On that hardware, a .NET application should be able to serve about 200-400 requests per second. If you have only a few hundred users, I doubt you are seeing even 2 requests per second, so I think you have a lot of capacity on that box, even with SQL server running.
Without know all of the details, I would say no, you will not see any performance improvement by adding servers.
By the way, if you're not using the Output Cache, I would start there.