I just started learning Memory Management and have an idea of page,frames,virtual memory and so on but I'm not understanding the procedure from changing logical addresses to their corresponding page numbers,
Here is the scenario-
Page Size = 100 words /8000 bits?
Process generates this logical address:
10 11 104 170 73 309 185 245 246 434 458 364
Process takes up two page frames,and that none of its are resident (in page frames) when the process begins execution.
Determine the page number corresponding to each logical address and fill them into a table with one row and 12 columns.
I know the answer is :
0 0 1 1 0 3 1 2 2 4 4 3
But can someone explain how this is done? Is there a equation or something? I remember seeing something with a table and changing things to binary and putting them in the page table like 00100 in Page 1 but I am not really sure. Graphical representations of how this works would be more than appreciated. Thanks
Related
With a Postscript driver (Xerox, Canon, HP, all), when I create a PS file, for example when I print the test page in the printer properties, I get :
OK :
The view of the result is correct (with GSview for example)
Not OK :
The file size is to big, more than 4 MB.
When I edit the file, I have one big image (doNimage). I think is the reason of the big size file.
The example file : https://drive.google.com/open?id=0B9bet657DEU5alV6WFZZdDFjMmc
I'm on Windows 10, similar problem with Windows server 2012 r2.
I let the configuration of the driver by default.
Anyone has an idea ?
Thanks a lot.
Regards.
I don't understand your problem, the file you posted a link to contains text. Here's an example:
360 4485 M <202530360E0F1102381030100D100B0824152D30103102020C302A1E19181B1E1730132E28301530132D3B02230B2A2E22081308>[46 16 28 70 18 42 44 44 54 32 28 32 36 32 25 39 65 40 40 28 32 44 44 44 18 28 53 45 20 47 38 45
40 28 34 40 40 28 40 28 34 40 18 44 44 25 53 40 16 39 34 0]xS
M is a moveto and xS uses the xshow operator to draw the glyphs represented by the character codes in the hexstring, using the values in the array to modify the width of each glyph.
If you were expecting to see ASCII character codes you are going to be sadly disappointed, the files uses an incrementally downloaded subset TrueType font, so the character codes are defined as they are encountered, that is the first glyph used will be given character code 1, the second will be character code 2 and so on.
Even without that, using ASCII would limit the languages that could be supported. Back in the 1980s that maybe didn't seem like a problem, but its a long time since that was considered acceptable.
If you were expecting to be able to modify the text by editing it in a text editor, forget it. PostScript is a programming language, and the output of a PostScript printer driver is a machine-generated program. Its a lengthy process for a skilled user of the language to decipher what the program is doing. The program is not amenable to alteration, if there's a fault in the output, correct the original document and recreate the PostScript program from the original.
PostScript is not an editable format.
Thanks all for your response. I see I was not very clear in my question.
Here is the state :
With the PS driver, on a windows server 2008, I get this file :
http://expirebox.com/download/0bb511565377e8b74eead67641fe7f68.html
Inside the file I can see the text "Page de test d\222imprimante"
On a Windows server 2012 R2 :
http://expirebox.com/download/60fa957cba97c82bbcd5c0e975825b52.html
I can't see any text. It's a printer page test too.
I need to see text because I'll print document with code inside. Code for a printer to identify page type. (for example a white page for the tray n° 1, yellow page for tray 2)
KenS : I understand your point. But why the same driver give different file.
I checked if it's really the same. The only difference I see is the OS, one x86, the other x64.
Thanks.
Regards.
I have a list of sporting matches by time with result and margin. I want Tableau to keep a running count of number of matches since the last x (say, since the last draw - where margin = 0).
This will mean that on every record, the running count will increase by one unless that match is a draw, in which case it will drop back to zero.
I have not found a method of achieving this. The only way I can see to restart counts is via dates (e.g. a new year).
As an aside, I can easily achieve this by creating a running count tally OUTSIDE of Tableau.
The interesting thing is that Tableau then doesn't quite deal with this well with more than one result on the same day.
For example, if the structure is:
GameID Date Margin Running count
...
48 01-01-15 54 122
49 08-01-15 12 123
50 08-01-15 0 124
51 08-01-15 17 0
52 08-01-15 23 1
53 15-01-15 9 2
...
Then when trying to plot running count against date, Tableau rearranges the data to show:
GameID Date Margin Running count
...
48 01-01-15 54 122
51 08-01-15 17 0
52 08-01-15 23 1
49 08-01-15 12 123
50 08-01-15 0 124
53 15-01-15 9 2
...
I assume it is doing this because by default it sorts the running count data in ascending order when dates are identical.
I'm using Ipython parallel in an optimisation algorithm that loops a large number of times. Parallelism is invoked in the loop using the map method of a LoadBalancedView (twice), a DirectView's dictionary interface and an invocation of a %px magic. I'm running the algorithm in an Ipython notebook.
I find that the memory consumed by both the kernel running the algorithm and one of the controllers increases steadily over time, limiting the number of loops I can execute (since available memory is limited).
Using heapy, I profiled memory use after a run of about 38 thousand loops:
Partition of a set of 98385344 objects. Total size = 18016840352 bytes.
Index Count % Size % Cumulative % Kind (class / dict of class)
0 5059553 5 9269101096 51 9269101096 51 IPython.parallel.client.client.Metadata
1 19795077 20 2915510312 16 12184611408 68 list
2 24030949 24 1641114880 9 13825726288 77 str
3 5062764 5 1424092704 8 15249818992 85 dict (no owner)
4 20238219 21 971434512 5 16221253504 90 datetime.datetime
5 401177 0 426782056 2 16648035560 92 scipy.optimize.optimize.OptimizeResult
6 3 0 402654816 2 17050690376 95 collections.defaultdict
7 4359721 4 323814160 2 17374504536 96 tuple
8 8166865 8 196004760 1 17570509296 98 numpy.float64
9 5488027 6 131712648 1 17702221944 98 int
<1582 more rows. Type e.g. '_.more' to view.>
You can see that about half the memory is used by IPython.parallel.client.client.Metadata instances. A good indicator that results from the map invocations are being cached is the 401177 OptimizeResult instances, the same number as the number of optimize invocations via lbview.map - I am not caching them in my code.
Is there a way I can control this memory usage on both the kernel and the Ipython parallel controller (who'se memory consumption is comparable to the kernel)?
Ipython parallel clients and controllers store past results and other metadata from past transactions.
The IPython.parallel.Client class provides a method for clearing this data:
Client.purge_everything()
documented here. There is also purge_results() and purge_local_results() methods that give you some control over what gets purged.
Here is a sample of my CSV
10820 0 0 0 0
10900 2 4 4 4
11000 21 50 54 58
11100 23 54 59 63
11200 25 59 63 68
11300 27 63 68 73
11400 29 68 73 78
11500 31 72 78 83
11600 32 76 82 88
11700 34 81 87 93
I'm looking to create to use xcode to retreive one line of code from this very lengthy CSV based on the first line.
For example:
if the user enters "10900", the second line columns will be returned.
If the user returns 11650, the 11600 line columns will be returned...always taking the lower line when the input value is less then the following line.
Any help would be appreciated. I've seen code to parse an entire CSV file, but I'm thinking this may be a big memory drain, right now my CSV has 2000 lines of values, which are all in ascending order based on the first column.
You have to load a file into memory anyways to find correct value.
With such a big CSV file I would recommend to turn CSV file into binary file (plist file for example) and put it as binary into your application - instead of parsing it each time in RunTime. It has much better performance and it's easier to work with that since you are working directly with NSDictonaries an NSArrays.
If you don't want to do it for some reason, the next solution is to use something like CHCSVParser:
https://github.com/davedelong/CHCSVParser
It provides optimization for loading only part of file at a time - which is the optimization you might be looking for.
Can someone explain this in a practical way? Sample represents usage for one, low-traffic Rails site using Nginx and 3 Mongrel clusters. I ask because I am aiming to learn about page caching, wondering if these figures have significant meaning to that process. Thank you. Great site!
me#vps:~$ free -m
total used free shared buffers cached
Mem: 512 506 6 0 15 103
-/+ buffers/cache: 387 124
Swap: 1023 113 910
Physical memory is all used up. Why? Because it's there, the system should be using it.
You'll note also that the system is using 113M of swap space. Bad? Good? It depends.
See also that there's 103M of cached disk; this means that the system has decided that it's better to cache 103M of disk and swap out these 113M; maybe you have some processes using memory that are not being used and thus are paged out to disk.
As the other poster said, you should be using other tools to see what's happening:
Your perception: is the site running appropiately when you use it?
Benchmarking: what response times are your clients seeing?
More fine-grained diagnostics:
top: you can see live which processes are using memory and CPU
vmstat: it produces this kind of output:
alex#armitage:~$ vmstat 1
procs -----------memory---------- ---swap-- -----io---- -system-- ----cpu----
r b swpd free buff cache si so bi bo in cs us sy id wa
2 1 71184 156520 92524 316488 1 5 12 23 362 250 13 6 80 1
0 0 71184 156340 92528 316508 0 0 0 1 291 608 10 1 89 0
0 0 71184 156364 92528 316508 0 0 0 0 308 674 9 2 89 0
0 0 71184 156364 92532 316504 0 0 0 72 295 723 9 0 91 0
1 0 71184 150892 92532 316508 0 0 0 0 370 722 38 0 62 0
0 0 71184 163060 92532 316508 0 0 0 0 303 611 17 2 81 0
which will show you whether swap is hurting you (high numbers on si, so) and a more easier to see performance-over-time statistic.
by my reading of this, you have used almost all your memory, have 6 M free, and are going into about 10% of your swap. A more useful tools is to use top or perhaps ps to see how much each of your individual mongrels are using in RAM. Because you're going into swap, you're probably getting more slowdowns. you might find having only 2 mongrels rather than 3 might actually respond faster because it likely wouldn't go into swap memory.
Page caching will for sure help a tonne on response time, so if your pages are cachable (eg, they don't have content that is unique to the individual user) I would say for sure check it out