I have studied in my operating systems class that Larger page tables can be implemented in memory management technique by using paging. When implementing this virtual memory does it really become slow memory access when it is implemented on a secondary storage device. I want to know the reason for it that how it slows down memory access? When we implement large page tables on secondary storage device.
Even smaller page tables can be (and have been) implemented using paging. The architectural issue is how to get around the chicken and egg problem of page tables being in virtual memory while referring to physical memory. A number of techniques have been developed to deal with that.
Paged page tables only slows down the memory when a page table access causes a page fault. Once the page fault is serviced, subsequent references to not trigger a page fault (unless the table is paged out). Paine the page tables is not slowing down the system constantly.
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I just learned about memory management and I am currently trying to figure out what Page Table is. Per my understanding, Page Table is a data structure that works just like hash tables, used to map and connect both logical and physical memory address in an Operating System.
We will need one register to determine the location of a page table of a process. But how many registers do we need to determine the location of a multilevel page table, for example a two and three level page table? How do you determine it?
Also, how will cache (L1-L3) in the processor affect memory reference access to page table? Will the majorities miss or hit? Why does it happen?
I tried to find references for this, but it leads me to TLB and I haven't learned about it yet. Might say that I am really beginner in OS. Help :)
Based on Nate's answer, we only need one register at the top level of the table, and the entries in the table are pointers to the next levels so there won't be any needs of more than one register in any level of page table.
I'm wondering how the cache (memory) gets warmed up. I understand that MongoDB uses memory mapped files and the OS's virtual memory to swap pages in and out as needed. What I don't understand is how it gets warmed up on startup.
Upon startup does mongod map all of the pages in the database to virtual memory or is there some other mechanism to load pages that are not yet mapped which get mapped as queries are run against the database?
Similarly, is the size of the database limited to the amount of virtual memory available to the system. I understand that on a 64-bit system this is a lot. Is there another mechanism other than memory mapping for pages to moved to and from disk?
Memory mapping means that there is a representation of all the on disk files available but only a portion of these files may be present in RAM. When a given page is needed (and it is not in RAM) it can be read from disk into RAM to be accessed.
Regarding limitations, you can see them on the MongoDB limits page
MongoDB does not do any specific "warming" of pages on startup, as it does not have any concept of which pages would be useful and which not.
If you wish to "Warm" certain collections manually before using them you should look at the touch command.
I am developing an app for S40, focused to work in the Nokia Ahsa 305. In some pages of the app, I show some tables filled with so many data (21 rows with 10 columns, like 210 Label data). When I show that table the memory use, rise a lot and when I try to show again the table, it gives me OutOfMemoryException.
Are there some guidelines that can be carried out for efficient memory management?
Here you can find some images from my memory diagram.
Before showing the table:
When I show the table:
After going back of the Table form
Memory shouldn't rise noticeably on that amount of data. I would doubt a table like this should take more than 200kb of memory unless you use images in some of the labels in which case it will take more.
A Component in Codename One shouldn't take more than 1kb since it doesn't have many fields within it, however if you have very long strings in every component (which I doubt since they won't be visible for a 200 component table).
You might have a memory leak which explains why the ram isn't collected although its hard to say from your description.
We had an issue with EncodedImage's in LWUIT 1.5 which we fixed in Codename One, however as far as I understood the Nokia guys removed the usage of EncodedImage's in Codename One resources which would really balloon memory usage for images.
I am working on a page cache replacement policy, I read many existing algorithms most of them are prefer to retain modified pages in cache. I don't really understand the reason behind it. Is it due to eviction cost or modified pages have higher chance of being used again?
Out of many different policies LRU(least recently used) policy provides good result with hardware support.
Is it due to eviction cost or modified pages have higher chance of being used again?
Yes
So according to locality of reference the recently modified page has more chances of being referenced again.
One more reason of retaining modified page in cache is that every page replacement of modified page (which has higher chances of being referenced again)requires two transfers. Firstly it is written into disk and secondly requested page comes in main memory. This very costly. But in case of non modified page (which has low chances of being referenced) only one transfer takes place i.e. requested page comes in memory.
I activated the wicket DebugBar in order to trace my session size. When I navigate on the web site, the indicated session size is stable at about 25k.
In the same time, the pagemap serialiazed on the disk continuously grows from about 25k for each page view.
What does that means? From what I understood, the pagemap on disk keeps all the pages. But why the session stays always at about 25k.
What is the impact on a big website. If I have 1000 parallel web sessions, the web server will need 25Mo to hold them and the disk 250Mo (10 pages * 25k * 1000)?
I will make some load test to check.
The debug bar value is telling you the size of your session in memory. As you browse to another page, the old page is serialized to the session store. This provides, among other things, back button support without killing your memory footprint.
So, to answer your first question, the size on disk grows because it is holding historical data while your session stays about the same because it is holding active data.
To answer your second question, its been some time since I have looked at it, but I believe the disk session store is capped at 10MB or so. Furthermore, you can change the behavior of the session store to meet your needs, but that's a whole different discussion.
See this Wiki page which describes the storage mechanisms in Wicket 1.5. It is a bit different than 1.4 but there is no such document for 1.4
Update: the Wiki page has been moved to the guide: https://ci.apache.org/projects/wicket/guide/7.x/guide/internals.html#pagestoring