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  • Decreasing cached memory and increasing Free memory in RAM

    - by Greenhorn
    Hi, Im using windows 2007 server 64 bit OS, I've uploaded the snap shot of my task manager when minimum processes running It shows Total memory 8190 mb *Cached memory 4315 mb* Free 3402 mb So effectively I get only 3402 mb of total RAM usage My question here is more than half is used for cached memory is there any means I can decrease this cached memory inturn I can increase my free memory. I need to do this because my Application requires at least 5GB RAM and it crashed when run in this system. Please give me a solution for this Thanks in advance

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  • NSCFString Memory Leak

    - by Lakshmie
    Hello, I have been solving a lot of memory leaks but have been unsuccessful in solving this one. There are tons of NSCF memory leaks coming due to [NSCFString substringWithRange:]. I have been checking all the String allocations and have released all of them at appropriate places. The responsible library: Foundation. Has anyone encountered this problem before? Can anyone suggest me as how I should takle this issue? Thanks, Lakshmie

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  • SQL SERVER – Introduction to SQL Server 2014 In-Memory OLTP

    - by Pinal Dave
    In SQL Server 2014 Microsoft has introduced a new database engine component called In-Memory OLTP aka project “Hekaton” which is fully integrated into the SQL Server Database Engine. It is optimized for OLTP workloads accessing memory resident data. In-memory OLTP helps us create memory optimized tables which in turn offer significant performance improvement for our typical OLTP workload. The main objective of memory optimized table is to ensure that highly transactional tables could live in memory and remain in memory forever without even losing out a single record. The most significant part is that it still supports majority of our Transact-SQL statement. Transact-SQL stored procedures can be compiled to machine code for further performance improvements on memory-optimized tables. This engine is designed to ensure higher concurrency and minimal blocking. In-Memory OLTP alleviates the issue of locking, using a new type of multi-version optimistic concurrency control. It also substantially reduces waiting for log writes by generating far less log data and needing fewer log writes. Points to remember Memory-optimized tables refer to tables using the new data structures and key words added as part of In-Memory OLTP. Disk-based tables refer to your normal tables which we used to create in SQL Server since its inception. These tables use a fixed size 8 KB pages that need to be read from and written to disk as a unit. Natively compiled stored procedures refer to an object Type which is new and is supported by in-memory OLTP engine which convert it into machine code, which can further improve the data access performance for memory –optimized tables. Natively compiled stored procedures can only reference memory-optimized tables, they can’t be used to reference any disk –based table. Interpreted Transact-SQL stored procedures, which is what SQL Server has always used. Cross-container transactions refer to transactions that reference both memory-optimized tables and disk-based tables. Interop refers to interpreted Transact-SQL that references memory-optimized tables. Using In-Memory OLTP In-Memory OLTP engine has been available as part of SQL Server 2014 since June 2013 CTPs. Installation of In-Memory OLTP is part of the SQL Server setup application. The In-Memory OLTP components can only be installed with a 64-bit edition of SQL Server 2014 hence they are not available with 32-bit editions. Creating Databases Any database that will store memory-optimized tables must have a MEMORY_OPTIMIZED_DATA filegroup. This filegroup is specifically designed to store the checkpoint files needed by SQL Server to recover the memory-optimized tables, and although the syntax for creating the filegroup is almost the same as for creating a regular filestream filegroup, it must also specify the option CONTAINS MEMORY_OPTIMIZED_DATA. Here is an example of a CREATE DATABASE statement for a database that can support memory-optimized tables: CREATE DATABASE InMemoryDB ON PRIMARY(NAME = [InMemoryDB_data], FILENAME = 'D:\data\InMemoryDB_data.mdf', size=500MB), FILEGROUP [SampleDB_mod_fg] CONTAINS MEMORY_OPTIMIZED_DATA (NAME = [InMemoryDB_mod_dir], FILENAME = 'S:\data\InMemoryDB_mod_dir'), (NAME = [InMemoryDB_mod_dir], FILENAME = 'R:\data\InMemoryDB_mod_dir') LOG ON (name = [SampleDB_log], Filename='L:\log\InMemoryDB_log.ldf', size=500MB) COLLATE Latin1_General_100_BIN2; Above example code creates files on three different drives (D:  S: and R:) for the data files and in memory storage so if you would like to run this code kindly change the drive and folder locations as per your convenience. Also notice that binary collation was specified as Windows (non-SQL). BIN2 collation is the only collation support at this point for any indexes on memory optimized tables. It is also possible to add a MEMORY_OPTIMIZED_DATA file group to an existing database, use the below command to achieve the same. ALTER DATABASE AdventureWorks2012 ADD FILEGROUP hekaton_mod CONTAINS MEMORY_OPTIMIZED_DATA; GO ALTER DATABASE AdventureWorks2012 ADD FILE (NAME='hekaton_mod', FILENAME='S:\data\hekaton_mod') TO FILEGROUP hekaton_mod; GO Creating Tables There is no major syntactical difference between creating a disk based table or a memory –optimized table but yes there are a few restrictions and a few new essential extensions. Essentially any memory-optimized table should use the MEMORY_OPTIMIZED = ON clause as shown in the Create Table query example. DURABILITY clause (SCHEMA_AND_DATA or SCHEMA_ONLY) Memory-optimized table should always be defined with a DURABILITY value which can be either SCHEMA_AND_DATA or  SCHEMA_ONLY the former being the default. A memory-optimized table defined with DURABILITY=SCHEMA_ONLY will not persist the data to disk which means the data durability is compromised whereas DURABILITY= SCHEMA_AND_DATA ensures that data is also persisted along with the schema. Indexing Memory Optimized Table A memory-optimized table must always have an index for all tables created with DURABILITY= SCHEMA_AND_DATA and this can be achieved by declaring a PRIMARY KEY Constraint at the time of creating a table. The following example shows a PRIMARY KEY index created as a HASH index, for which a bucket count must also be specified. CREATE TABLE Mem_Table ( [Name] VARCHAR(32) NOT NULL PRIMARY KEY NONCLUSTERED HASH WITH (BUCKET_COUNT = 100000), [City] VARCHAR(32) NULL, [State_Province] VARCHAR(32) NULL, [LastModified] DATETIME NOT NULL, ) WITH (MEMORY_OPTIMIZED = ON, DURABILITY = SCHEMA_AND_DATA); Now as you can see in the above query example we have used the clause MEMORY_OPTIMIZED = ON to make sure that it is considered as a memory optimized table and not just a normal table and also used the DURABILITY Clause= SCHEMA_AND_DATA which means it will persist data along with metadata and also you can notice this table has a PRIMARY KEY mentioned upfront which is also a mandatory clause for memory-optimized tables. We will talk more about HASH Indexes and BUCKET_COUNT in later articles on this topic which will be focusing more on Row and Index storage on Memory-Optimized tables. So stay tuned for that as well. Now as we covered the basics of Memory Optimized tables and understood the key things to remember while using memory optimized tables, let’s explore more using examples to understand the Performance gains using memory-optimized tables. I will be using the database which i created earlier in this article i.e. InMemoryDB in the below Demo Exercise. USE InMemoryDB GO -- Creating a disk based table CREATE TABLE dbo.Disktable ( Id INT IDENTITY, Name CHAR(40) ) GO CREATE NONCLUSTERED INDEX IX_ID ON dbo.Disktable (Id) GO -- Creating a memory optimized table with similar structure and DURABILITY = SCHEMA_AND_DATA CREATE TABLE dbo.Memorytable_durable ( Id INT NOT NULL PRIMARY KEY NONCLUSTERED Hash WITH (bucket_count =1000000), Name CHAR(40) ) WITH (MEMORY_OPTIMIZED = ON, DURABILITY = SCHEMA_AND_DATA) GO -- Creating an another memory optimized table with similar structure but DURABILITY = SCHEMA_Only CREATE TABLE dbo.Memorytable_nondurable ( Id INT NOT NULL PRIMARY KEY NONCLUSTERED Hash WITH (bucket_count =1000000), Name CHAR(40) ) WITH (MEMORY_OPTIMIZED = ON, DURABILITY = SCHEMA_only) GO -- Now insert 100000 records in dbo.Disktable and observe the Time Taken DECLARE @i_t bigint SET @i_t =1 WHILE @i_t<= 100000 BEGIN INSERT INTO dbo.Disktable(Name) VALUES('sachin' + CONVERT(VARCHAR,@i_t)) SET @i_t+=1 END -- Do the same inserts for Memory table dbo.Memorytable_durable and observe the Time Taken DECLARE @i_t bigint SET @i_t =1 WHILE @i_t<= 100000 BEGIN INSERT INTO dbo.Memorytable_durable VALUES(@i_t, 'sachin' + CONVERT(VARCHAR,@i_t)) SET @i_t+=1 END -- Now finally do the same inserts for Memory table dbo.Memorytable_nondurable and observe the Time Taken DECLARE @i_t bigint SET @i_t =1 WHILE @i_t<= 100000 BEGIN INSERT INTO dbo.Memorytable_nondurable VALUES(@i_t, 'sachin' + CONVERT(VARCHAR,@i_t)) SET @i_t+=1 END The above 3 Inserts took 1.20 minutes, 54 secs, and 2 secs respectively to insert 100000 records on my machine with 8 Gb RAM. This proves the point that memory-optimized tables can definitely help businesses achieve better performance for their highly transactional business table and memory- optimized tables with Durability SCHEMA_ONLY is even faster as it does not bother persisting its data to disk which makes it supremely fast. Koenig Solutions is one of the few organizations which offer IT training on SQL Server 2014 and all its updates. Now, I leave the decision on using memory_Optimized tables on you, I hope you like this article and it helped you understand  the fundamentals of IN-Memory OLTP . Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: PostADay, SQL, SQL Authority, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL Tagged: Koenig

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  • sizes of RAM, of virtual memory and of swap for 32-bit OS

    - by Tim
    If I understand correctly, a 32-bit OS (Ubuntu) can only address 4GiB memory, so RAM with size larger than 4Gib will only be used 4Gib of itself and the rest is a waste. I am now confused about this situation for RAM with similar one for virtual memory and for swap. with virtual memory being swap + RAM, if the size of the virtual memory exceeds 4Gib, will the exceeding part be a waste for the 32-bit OS? if I now have to choose the size for my swap partition, is it a factor to consider that the 32-bit OS can only address 4GiB memory? Does the size of swap have to be chosen with respect to the 4Gib addressible limitation? Will the swap exceeding 4GiB always be a waste? is virtual memory equal to RAM and swap? or can virtual memory use space on the hard drive outside the swap partition? Thanks and regards!

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  • Does scheduling recycling app pool in IIS7 help the server conserve memory better?

    - by user29266
    Hello, I have a VPS (IIS7 with Win 2008) It's got: 40 websites and a SQL Server 2008 powering them with only 2 Gigs of RAM. None of the sites are mission critical, they are all just demos. I often have ram issues on the server because each site has does caching and generally uses a lot of memory. Would it make sense to set the application pools to recycle every 3 hours? I'm sure this would free up any memory leaks or processes left "hanging" Are there any other tips on this? Thank you very much!, Aron

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  • Loads of memory in "standby" on Windows Server 2008 R2

    - by Jaap
    In our SharePoint farm, our Web Front End servers all have loads of memory in "standby" mode, meaning very little is available for our IIS worker process. We have 32 GB of RAM in each of the boxes, and standby memory will creep up to about 28 GB, whereas the IIS worker process only seems to be using about 2 GB. Also, we've seen the machine use the swap file extensively while this memory was in standby, so I am starting to think that this memory in standby mode is stopping IIS from using it, forcing it to swap to disk, causing more performance problems. I used SysInternals RamMap to indentify what is being kept in memory, and it was able to tell me that almost everything in standby memory is of type "Mapped File". When I sort the files listed under the file summary tab in RamMap by file size, the largest files (around a few hundred meg each) are IIS log files and SharePoint log files. I would like to understand which process is loading these files into standby memory and why they are not being released. When I do an iisreset, it does not release the memory. Any ideas? Thanks!

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  • Memory Usage of SQL Server

    - by Ashish
    SQL Server instance on my server is using almost full memory available in my Physical Server. Say if i am having 8GB of RAM than SQL Server is using 7.8 GB of RAM from system. I also have read articles and also read many similar questions regarding same on this forum and i understand that memory is reserved and it is using memory. But i have 2 same servers and 2 SQL Servers, why this is happening on a single SQL Instance not on other. Also when i run DBCC MemoryStatus than it is showing up... VM Reserved 8282008 VM Committed 537936 so from this we know that SQL reserved whole 8GB memory, but why this VM Committed keeps increasing. What i understand is VM Committed is: VM Committed: This value shows the overall amount of VAS that SQL Server has committed. VAS that is committed has been associated with physical memory. So this is the memory SQL Server has committed (from this i understand that physical memory actually SQL Server is using at instance). So like to know the reason behind this ever increasing VM Committed memory on my server and not on another. Thanks in Advance.

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  • Yet another Memory Leak Issue (memory is still gone when program terminates)- C program on SLES

    - by user1426181
    I run my C program on Suse Linux Enterprise that compresses several thousand large files (between 10MB and 100MB in size), and the program gets slower and slower as the program runs (it's running multi-threaded with 32 threads on a Intel Sandy Bridge board). When the program completes, and it's run again, it's still very slow. When I watch the program running, I see that the memory is being depleted while the program runs, which you would think is just a classic memory leak problem. But, with a normal malloc()/free() mismatch, I would expect all the memory to return when the program terminates. But, most of the memory doesn't get reclaimed when the program completes. The free or top command shows Mem: 63996M total, 63724M used, 272M free when the program is slowed down to a halt, but, after the termination, the free memory only grows back to about 3660M. When the program is rerun, the free memory is quickly used up. The top program only shows that the program, while running, is using at most 4% or so of the memory. I thought that it might be a memory fragmentation problem, but, I built a small test program that simulates all the memory allocation activity in the program (many randomized aspects were built in - size/quantity), and it always returns all the memory upon completion. So, I don't think that's it. Questions: Can there be a malloc()/free() mismatch that will lose memory permanently, i.e. even after the process completes? What other things in a C program (not C++) can cause permanent memory loss, i.e. after the program completes, and even the terminal window closes? Only a reboot brings the memory back. I've read other posts about files not being closed causing problems, but, I don't think I have that problem. Is it valid to be looking at top and free for the memory statistics, i.e. do they accurately describe the memory situation? They do seem to correspond to the slowness of the program. If the program only shows a 4% memory usage, will something like valgrind find this problem?

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  • Virtual memory on Linux doesn't add up?

    - by Brendan Long
    I was looking at System Monitor on Linux and noticed that Firefox is using 441 MB of memory, and several other applications are using 274, 257, 232, etc (adding up to over 3 GB of virtual memory). So I switch over to the Resources tab, and it says I'm using 462 MB of memory and not touching swap. I'm confused. What does the virtual memory amount mean then if the programs aren't actually using it. I was thinking maybe memory they've requested but aren't using, but how would the OS know that? I can't think of any "I might need this much memory in the future" function..

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  • Free / Cached / Available memory on Linux

    - by pkoraca
    I have read that linux uses free memory for caching, to make system faster. However, both Nagios and Paessler PRTG monitoring system show me that my memory usage is critical. I could change Nagios mem_usage script to sum free and cached memory, but would that be correct information? I doubt that they misunderstood Linux memory usage. Lets say I have 8 GB RAM. 5 GB are used, 2 GB is cached, and I have 1 GB of free memory. Real available memory should be free+cached (3 GB)? If some new application would need additional 3 GB RAM, could it take everything from cache and free without using swap, or is there a minimum that should be in cache? Real example: $ cat /proc/meminfo MemTotal: 5984256 kB MemFree: 137052 kB Buffers: 140484 kB Cached: 3439616 kB SwapCached: 244 kB Active: 3148824 kB Inactive: 2341768 kB ... My monitoring tools show that I have 137 MB free RAM, however I have ~3,5 GB in Cache. Thanks!

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  • How UIWindow#addSubview can make memory leak?

    - by Jakub
    Hello, I started to learn using Instrument, but I cannot figure it out. After I start my application, the UI shows up, I do nothing and after few seconds I can see memory leak detected: When I have a look at the second leak I can see the following stack: When I double click on the cell related to my code I can see that it is pointing to the following line of code: [window addSubview:newPostUIViewController.view]; from the method: - (void)applicationDidFinishLaunching:(UIApplication *)application { //creating view controller newPostUIViewController = [[NewPostUIViewController alloc] initWithNibName:@"NewPostView" bundle:nil]; newPostUIViewController.title = @"Post it!"; [window addSubview:newPostUIViewController.view]; // Override point for customization after application launch [window makeKeyAndVisible]; } I wonder, how this can be a reason of a leak? I release newPostUIViewController in the dealloc method of PostItAppDelegate class. Any ideas how this could be explained?

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  • Ubuntu Linux: Process swap memory and memory usage

    - by David Halter
    My Ubuntu eats more memory than the task manager is showing: sudo ps -e --format rss | awk 'BEGIN{c=0} {c+=$1} END{print c/1024}' 1043.84 free -m total used free shared buffers cached Mem: 3860 1878 1982 0 20 679 -/+ buffers/cache: 1178 2681 Swap: 2729 1035 1693 That's strange. Can someone explain this difference? But what is more important: I'd like to know how much memory a process is really using. I don't want to know the virtual memory size, but rather the resident memory plus swap of a process. I have also tried to output the format param "sz" of 'ps', but the sum of this is to high (5450 MB) (param 'size' gives 8323.45 MB). Are there any other options? I really want to use this, to determine which programs/processes are eating to much memory (and swap), to kill them, because hibernate might not be working if the swap partition is to little.

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  • Problem with memory leaks

    - by user191723
    Sorry, having difficulty formattin code to appear correct here??? I am trying to understand the readings I get from running instruments on my app which are telling me I am leaking memory. There are a number, quite a few in fact, that get reported from inside the Foundation, AVFoundation CoreGraphics etc that I assume I have no control over and so should ignore such as: Malloc 32 bytes: 96 bytes, AVFoundation, prepareToRecordQueue or Malloc 128 bytes: 128 bytes, CoreGraphics, open_handle_to_dylib_path Am I correct in assuming these are something the system will resolve? But then there are leaks that are reported that I believe I am responsible for, such as: This call reports against this line leaks 2.31KB [self createAVAudioRecorder:frameAudioFile]; Immediately followed by this: -(NSError*) createAVAudioRecorder: (NSString *)fileName { // flush recorder to start afresh [audioRecorder release]; audioRecorder = nil; // delete existing file to ensure we have clean start [self deleteFile: fileName]; VariableStore *singleton = [VariableStore sharedInstance]; // get full path to target file to create NSString *destinationString = [singleton.docsPath stringByAppendingPathComponent: fileName]; NSURL *destinationURL = [NSURL fileURLWithPath: destinationString]; // configure the recording settings NSMutableDictionary *recordSettings = [[NSMutableDictionary alloc] initWithCapacity:6]; //****** LEAKING 384 BYTES [recordSettings setObject:[NSNumber numberWithInt:kAudioFormatLinearPCM] forKey: AVFormatIDKey]; //***** LEAKING 32 BYTES float sampleRate = 44100.0; [recordSettings setObject:[NSNumber numberWithFloat: sampleRate] forKey: AVSampleRateKey]; //***** LEAKING 48 BYTES [recordSettings setObject:[NSNumber numberWithInt:2] forKey:AVNumberOfChannelsKey]; int bitDepth = 16; [recordSettings setObject: [NSNumber numberWithInt:bitDepth] forKey:AVLinearPCMBitDepthKey]; //***** LEAKING 48 BYTES [recordSettings setObject:[NSNumber numberWithBool:YES] forKey:AVLinearPCMIsBigEndianKey]; [recordSettings setObject:[NSNumber numberWithBool: NO]forKey:AVLinearPCMIsFloatKey]; NSError *recorderSetupError = nil; // create the new recorder with target file audioRecorder = [[AVAudioRecorder alloc] initWithURL: destinationURL settings: recordSettings error: &recorderSetupError]; //***** LEAKING 1.31KB [recordSettings release]; recordSettings = nil; // check for erros if (recorderSetupError) { UIAlertView *alert = [[UIAlertView alloc] initWithTitle: @"Can't record" message: [recorderSetupError localizedDescription] delegate: nil cancelButtonTitle: @"OK" otherButtonTitles: nil]; [alert show]; [alert release]; alert = nil; return recorderSetupError; } [audioRecorder prepareToRecord]; //***** LEAKING 512 BYTES audioRecorder.delegate = self; return recorderSetupError; } I do not understand why there is a leak as I release audioRecorder at the start and set to nil and I release recordSettings and set to nil? Can anyone enlighten me please? Thanks

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  • Understanding the memory consumption on iPhone

    - by zoul
    Hello! I am working on a 2D iPhone game using OpenGL ES and I keep hitting the 24 MB memory limit – my application keeps crashing with the error code 101. I tried real hard to find where the memory goes, but the numbers in Instruments are still much bigger than what I would expect. I ran the application with the Memory Monitor, Object Alloc, Leaks and OpenGL ES instruments. When the application gets loaded, free physical memory drops from 37 MB to 23 MB, the Object Alloc settles around 7 MB, Leaks show two or three leaks a few bytes in size, the Gart Object Size is about 5 MB and Memory Monitor says the application takes up about 14 MB of real memory. I am perplexed as where did the memory go – when I dig into the Object Allocations, most of the memory is in the textures, exactly as I would expect. But both my own texture allocation counter and the Gart Object Size agree that the textures should take up somewhere around 5 MB. I am not aware of allocating anything else that would be worth mentioning, and the Object Alloc agrees. Where does the memory go? (I would be glad to supply more details if this is not enough.) Update: I really tried to find where I could allocate so much memory, but with no results. What drives me wild is the difference between the Object Allocations (~7 MB) and real memory usage as shown by Memory Monitor (~14 MB). Even if there were huge leaks or huge chunks of memory I forget about, the should still show up in the Object Allocations, shouldn’t they? I’ve already tried the usual suspects, ie. the UIImage with its caching, but that did not help. Is there a way to track memory usage “debugger-style”, line by line, watching each statement’s impact on memory usage? What I have found so far: I really am using that much memory. It is not easy to measure the real memory consumption, but after a lot of counting I think the memory consumption is really that high. My fault. I found no easy way to measure the memory used. The Memory Monitor numbers are accurate (these are the numbers that really matter), but the Memory Monitor can’t tell you where exactly the memory goes. The Object Alloc tool is almost useless for tracking the real memory usage. When I create a texture, the allocated memory counter goes up for a while (reading the texture into the memory), then drops (passing the texture data to OpenGL, freeing). This is OK, but does not always happen – sometimes the memory usage stays high even after the texture has been passed on to OpenGL and freed from “my” memory. This means that the total amount of memory allocated as shown by the Object Alloc tool is smaller than the real total memory consumption, but bigger than the real consumption minus textures (real – textures < object alloc < real). Go figure. I misread the Programming Guide. The memory limit of 24 MB applies to textures and surfaces, not the whole application. The actual red line lies a bit further, but I could not find any hard numbers. The consensus is that 25–30 MB is the ceiling. When the system gets short on memory, it starts sending the memory warning. I have almost nothing to free, but other applications do release some memory back to the system, especially Safari (which seems to be caching the websites). When the free memory as shown in the Memory Monitor goes zero, the system starts killing. I had to bite the bullet and rewrite some parts of the code to be more efficient on memory, but I am probably still pushing it. I

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  • Are memory leaks really something to worry about?

    - by chuck final
    I came across this post today, arguably debatable/wrong somewhat, but worth a shot looking over: http://andyharglesiscodebase.wordpress.com/2013/11/01/why-programmers-shouldnt-worry-about-memory-leaks/ The poster claims that modern OSes automatically have garbage collection implemented in the kernel memory, and that any unfreed user heap memory is managed during "post partum cleanup". It seems like rubbish, but I can't be 100% sure since I am not that knowledgeable on the kernel's memory management setup, etc.

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  • Why is Available Physical Memory (dwAvailPhys) > Available Virtual Memory (dwAvailVirtual) in call G

    - by Andrew
    I am playing with an MSDN sample to do memory stress testing (see: http://msdn.microsoft.com/en-us/magazine/cc163613.aspx) and an extension of that tool that specifically eats physical memory (see http://www.donationcoder.com/Forums/bb/index.php?topic=14895.0;prev_next=next). I am obviously confused though on the differences between Virtual and Physical Memory. I thought each process has 2 GB of virtual memory (although I also read 1.5 GB because of "overhead". My understanding was that some/all/none of this virtual memory could be physical memory, and the amount of physical memory used by a process could change over time (memory could be swapped out to disc, etc.)I further thought that, in general, when you allocate memory, the operating system could use physical memory or virtual memory. From this, I conclude that dwAvailVirtual should always be equal to or greater than dwAvailPhys in the call GlobalMemoryStatus. However, I often (always?) see the opposite. What am I missing. I apologize in advance if my question is not well formed. I'm still trying to get my head around the whole memory management system in Windows. Tutorials/Explanations/Book recs are most welcome! Andrew

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  • Can you force a crash if a write occurs to a given memory location with finer than page granularity?

    - by Joseph Garvin
    I'm writing a program that for performance reasons uses shared memory (alternatives have been evaluated, and they are not fast enough for my task, so suggestions to not use it will be downvoted). In the shared memory region I am writing many structs of a fixed size. There is one program responsible for writing the structs into shared memory, and many clients that read from it. However, there is one member of each struct that clients need to write to (a reference count, which they will update atomically). All of the other members should be read only to the clients. Because clients need to change that one member, they can't map the shared memory region as read only. But they shouldn't be tinkering with the other members either, and since these programs are written in C++, memory corruption is possible. Ideally, it should be as difficult as possible for one client to crash another. I'm only worried about buggy clients, not malicious ones, so imperfect solutions are allowed. I can try to stop clients from overwriting by declaring the members in the header they use as const, but that won't prevent memory corruption (buffer overflows, bad casts, etc.) from overwriting. I can insert canaries, but then I have to constantly pay the cost of checking them. Instead of storing the reference count member directly, I could store a pointer to the actual data in a separate mapped write only page, while keeping the structs in read only mapped pages. This will work, the OS will force my application to crash if I try to write to the pointed to data, but indirect storage can be undesirable when trying to write lock free algorithms, because needing to follow another level of indirection can change whether something can be done atomically. Is there any way to mark smaller areas of memory such that writing them will cause your app to blow up? Some platforms have hardware watchpoints, and maybe I could activate one of those with inline assembly, but I'd be limited to only 4 at a time on 32-bit x86 and each one could only cover part of the struct because they're limited to 4 bytes. It'd also make my program painful to debug ;)

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  • Too much memory consumed during TFS automated build

    - by Bernard Chen
    We're running TFS 2010 Standard Edition, and we've set up an automated build to run whenever someone checks in code. We run through all of the automated tests (built with MSTest) as part of the build. We've configured the build to run the tests as a 64-bit process, but the QTAgent.exe that runs the tests grows in memory while the tests are running. It is currently reaching 8GB for the ~650 tests we have, and the process has slowed significantly when we went from 450 tests to 650 tests. When we run all of the tests in the local development environment, memory seems to be freed at least with each TestClass and never exceeds a certain level. The process of running all tests has not increased significantly in the local development environment. Is there a way to configure the build service to free up memory with each Test or each TestClass? With the way things are currently running, the build process gets very slow when we start to run out of memory on the machine. Edit: I found the MSTest invocation in the build log and ran it manually and saw the same behavior of runaway memory. I removed the /publish, /publishbuild, /teamproject, /platform, and /flavor parameters from the invocation of MSTest, in case the test runner was holding onto results until the end, but the behavior didn't change. I ran the same command line on a dev box, separate from the build server, and the memory freed up frequently. It seems there must be something wrong/different about the build server that is causing it to behave different, but I'm stumped where to look. I've looked at qtagent.exe.config, mstest.exe.config, versions of both executables. What else might affect this?

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  • Automatically Kill/Restart Process(es) When Memory is Critically Low

    - by nemesisfixx
    I have a Debian Wheezy VPS box where am running a couple of Django apps in production. Ideally, would have tried addressed my current memory footprint issues by optimizing the apps, adding more RAM or augmenting with Swap. But the problem is that I doubt there's much memory optimization I'd milk from optimizing the Django apps (the stack being open-source and robust), and adding RAM is a cost constraint for me (this is a remote VPS), also, the host doesn't offer options to use Swap! So, in the meantime (as I wait to secure more resources to afford more RAM), I wish to mitigate the scenarios where the server runs out memory so that I just have to request a VPS restart (as in, at that point, I can't even SSH into the box!). So, what I would love in a solution is the ability to detect when a process (or generally, total system memory usage) exceeds a certain critical amount (for now, example the FREE RAM falls to say 10%) - which I've noticed occurs after the VPS's been up for long, and when also traffic is suddenly much to some of the heavy apps (most are just staging apps anyway). So, I wish to be able to kill/restart the offending process(es) - most likely Apache. Which solution when done manually in these situations has restored sane memory usage levels - a hint that possibly one or more of the Django apps has a memory leak? In brief: Monitor overall system RAM usage When FREE RAM falls below a given critical threshold (say below 10%), kill/restart the offending process(es) - or simpler, if we assume from my current log analysis (using linux-dash) that Apache is often the offender, then kill/restart it. Rinse and repeat...

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  • Reconciling vmware memory vs windows memory usage

    - by RyanW
    I have a Windows 2008 R2 64 bit virtual machine on ESXi 4.1 host. The host reports that the virtual machine is actively using less than 1 GB of memory. But, in Windows it's reporting the machine is using 7 GB of memory, even though the total of the processes listed in task manager is less than 1 GB. The machine is rather unresponsive and I'm concerned this is impacting other applications (server's purpose is to run ASP.NET state server process, which has been having trouble and led me to spot the memory question). I just noticed High memory usage Windows Server 2008r2 on VMware and will be looking through those documents more, but what is causing this?

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  • ANTS Memory Profiler 7.0 Review

    - by Michael B. McLaughlin
    (This is my first review as a part of the GeeksWithBlogs.net Influencers program. It’s a program in which I (and the others who have been selected for it) get the opportunity to check out new products and services and write reviews about them. We don’t get paid for this, but we do generally get to keep a copy of the software or retain an account for some period of time on the service that we review. In this case I received a copy of Red Gate Software’s ANTS Memory Profiler 7.0, which was released in January. I don’t have any upgrade rights nor is my review guided, restrained, influenced, or otherwise controlled by Red Gate or anyone else. But I do get to keep the software license. I will always be clear about what I received whenever I do a review – I leave it up to you to decide whether you believe I can be objective. I believe I can be. If I used something and really didn’t like it, keeping a copy of it wouldn’t be worth anything to me. In that case though, I would simply uninstall/deactivate/whatever the software or service and tell the company what I didn’t like about it so they could (hopefully) make it better in the future. I don’t think it’d be polite to write up a terrible review, nor do I think it would be a particularly good use of my time. There are people who get paid for a living to review things, so I leave it to them to tell you what they think is bad and why. I’ll only spend my time telling you about things I think are good.) Overview of Common .NET Memory Problems When coming to land of managed memory from the wilds of unmanaged code, it’s easy to say to one’s self, “Wow! Now I never have to worry about memory problems again!” But this simply isn’t true. Managed code environments, such as .NET, make many, many things easier. You will never have to worry about memory corruption due to a bad pointer, for example (unless you’re working with unsafe code, of course). But managed code has its own set of memory concerns. For example, failing to unsubscribe from events when you are done with them leaves the publisher of an event with a reference to the subscriber. If you eliminate all your own references to the subscriber, then that memory is effectively lost since the GC won’t delete it because of the publishing object’s reference. When the publishing object itself becomes subject to garbage collection then you’ll get that memory back finally, but that could take a very long time depending of the life of the publisher. Another common source of resource leaks is failing to properly release unmanaged resources. When writing a class that contains members that hold unmanaged resources (e.g. any of the Stream-derived classes, IsolatedStorageFile, most classes ending in “Reader” or “Writer”), you should always implement IDisposable, making sure to use a properly written Dispose method. And when you are using an instance of a class that implements IDisposable, you should always make sure to use a 'using' statement in order to ensure that the object’s unmanaged resources are disposed of properly. (A ‘using’ statement is a nicer, cleaner looking, and easier to use version of a try-finally block. The compiler actually translates it as though it were a try-finally block. Note that Code Analysis warning 2202 (CA2202) will often be triggered by nested using blocks. A properly written dispose method ensures that it only runs once such that calling dispose multiple times should not be a problem. Nonetheless, CA2202 exists and if you want to avoid triggering it then you should write your code such that only the innermost IDisposable object uses a ‘using’ statement, with any outer code making use of appropriate try-finally blocks instead). Then, of course, there are situations where you are operating in a memory-constrained environment or else you want to limit or even eliminate allocations within a certain part of your program (e.g. within the main game loop of an XNA game) in order to avoid having the GC run. On the Xbox 360 and Windows Phone 7, for example, for every 1 MB of heap allocations you make, the GC runs; the added time of a GC collection can cause a game to drop frames or run slowly thereby making it look bad. Eliminating allocations (or else minimizing them and calling an explicit Collect at an appropriate time) is a common way of avoiding this (the other way is to simplify your heap so that the GC’s latency is low enough not to cause performance issues). ANTS Memory Profiler 7.0 When the opportunity to review Red Gate’s recently released ANTS Memory Profiler 7.0 arose, I jumped at it. In order to review it, I was given a free copy (which does not include upgrade rights for future versions) which I am allowed to keep. For those of you who are familiar with ANTS Memory Profiler, you can find a list of new features and enhancements here. If you are an experienced .NET developer who is familiar with .NET memory management issues, ANTS Memory Profiler is great. More importantly still, if you are new to .NET development or you have no experience or limited experience with memory profiling, ANTS Memory Profiler is awesome. From the very beginning, it guides you through the process of memory profiling. If you’re experienced and just want dive in however, it doesn’t get in your way. The help items GAHSFLASHDAJLDJA are well designed and located right next to the UI controls so that they are easy to find without being intrusive. When you first launch it, it presents you with a “Getting Started” screen that contains links to “Memory profiling video tutorials”, “Strategies for memory profiling”, and the “ANTS Memory Profiler forum”. I’m normally the kind of person who looks at a screen like that only to find the “Don’t show this again” checkbox. Since I was doing a review, though, I decided I should examine them. I was pleasantly surprised. The overview video clocks in at three minutes and fifty seconds. It begins by showing you how to get started profiling an application. It explains that profiling is done by taking memory snapshots periodically while your program is running and then comparing them. ANTS Memory Profiler (I’m just going to call it “ANTS MP” from here) analyzes these snapshots in the background while your application is running. It briefly mentions a new feature in Version 7, a new API that give you the ability to trigger snapshots from within your application’s source code (more about this below). You can also, and this is the more common way you would do it, take a memory snapshot at any time from within the ANTS MP window by clicking the “Take Memory Snapshot” button in the upper right corner. The overview video goes on to demonstrate a basic profiling session on an application that pulls information from a database and displays it. It shows how to switch which snapshots you are comparing, explains the different sections of the Summary view and what they are showing, and proceeds to show you how to investigate memory problems using the “Instance Categorizer” to track the path from an object (or set of objects) to the GC’s root in order to find what things along the path are holding a reference to it/them. For a set of objects, you can then click on it and get the “Instance List” view. This displays all of the individual objects (including their individual sizes, values, etc.) of that type which share the same path to the GC root. You can then click on one of the objects to generate an “Instance Retention Graph” view. This lets you track directly up to see the reference chain for that individual object. In the overview video, it turned out that there was an event handler which was holding on to a reference, thereby keeping a large number of strings that should have been freed in memory. Lastly the video shows the “Class List” view, which lets you dig in deeply to find problems that might not have been clear when following the previous workflow. Once you have at least one memory snapshot you can begin analyzing. The main interface is in the “Analysis” tab. You can also switch to the “Session Overview” tab, which gives you several bar charts highlighting basic memory data about the snapshots you’ve taken. If you hover over the individual bars (and the individual colors in bars that have more than one), you will see a detailed text description of what the bar is representing visually. The Session Overview is good for a quick summary of memory usage and information about the different heaps. You are going to spend most of your time in the Analysis tab, but it’s good to remember that the Session Overview is there to give you some quick feedback on basic memory usage stats. As described above in the summary of the overview video, there is a certain natural workflow to the Analysis tab. You’ll spin up your application and take some snapshots at various times such as before and after clicking a button to open a window or before and after closing a window. Taking these snapshots lets you examine what is happening with memory. You would normally expect that a lot of memory would be freed up when closing a window or exiting a document. By taking snapshots before and after performing an action like that you can see whether or not the memory is really being freed. If you already know an area that’s giving you trouble, you can run your application just like normal until just before getting to that part and then you can take a few strategic snapshots that should help you pin down the problem. Something the overview didn’t go into is how to use the “Filters” section at the bottom of ANTS MP together with the Class List view in order to narrow things down. The video tutorials page has a nice 3 minute intro video called “How to use the filters”. It’s a nice introduction and covers some of the basics. I’m going to cover a bit more because I think they’re a really neat, really helpful feature. Large programs can bring up thousands of classes. Even simple programs can instantiate far more classes than you might realize. In a basic .NET 4 WPF application for example (and when I say basic, I mean just MainWindow.xaml with a button added to it), the unfiltered Class List view will have in excess of 1000 classes (my simple test app had anywhere from 1066 to 1148 classes depending on which snapshot I was using as the “Current” snapshot). This is amazing in some ways as it shows you how in stark detail just how immensely powerful the WPF framework is. But hunting through 1100 classes isn’t productive, no matter how cool it is that there are that many classes instantiated and doing all sorts of awesome things. Let’s say you wanted to examine just the classes your application contains source code for (in my simple example, that would be the MainWindow and App). Under “Basic Filters”, click on “Classes with source” under “Show only…”. Voilà. Down from 1070 classes in the snapshot I was using as “Current” to 2 classes. If you then click on a class’s name, it will show you (to the right of the class name) two little icon buttons. Hover over them and you will see that you can click one to view the Instance Categorizer for the class and another to view the Instance List for the class. You can also show classes based on which heap they live on. If you chose both a Baseline snapshot and a Current snapshot then you can use the “Comparing snapshots” filters to show only: “New objects”; “Surviving objects”; “Survivors in growing classes”; or “Zombie objects” (if you aren’t sure what one of these means, you can click the helpful “?” in a green circle icon to bring up a popup that explains them and provides context). Remember that your selection(s) under the “Show only…” heading will still apply, so you should update those selections to make sure you are seeing the view you want. There are also links under the “What is my memory problem?” heading that can help you diagnose the problems you are seeing including one for “I don’t know which kind I have” for situations where you know generally that your application has some problems but aren’t sure what the behavior you have been seeing (OutOfMemoryExceptions, continually growing memory usage, larger memory use than expected at certain points in the program). The Basic Filters are not the only filters there are. “Filter by Object Type” gives you the ability to filter by: “Objects that are disposable”; “Objects that are/are not disposed”; “Objects that are/are not GC roots” (GC roots are things like static variables); and “Objects that implement _______”. “Objects that implement” is particularly neat. Once you check the box, you can then add one or more classes and interfaces that an object must implement in order to survive the filtering. Lastly there is “Filter by Reference”, which gives you the option to pare down the list based on whether an object is “Kept in memory exclusively by” a particular item, a class/interface, or a namespace; whether an object is “Referenced by” one or more of those choices; and whether an object is “Never referenced by” one or more of those choices. Remember that filtering is cumulative, so anything you had set in one of the filter sections still remains in effect unless and until you go back and change it. There’s quite a bit more to ANTS MP – it’s a very full featured product – but I think I touched on all of the most significant pieces. You can use it to debug: a .NET executable; an ASP.NET web application (running on IIS); an ASP.NET web application (running on Visual Studio’s built-in web development server); a Silverlight 4 browser application; a Windows service; a COM+ server; and even something called an XBAP (local XAML browser application). You can also attach to a .NET 4 process to profile an application that’s already running. The startup screen also has a large number of “Charting Options” that let you adjust which statistics ANTS MP should collect. The default selection is a good, minimal set. It’s worth your time to browse through the charting options to examine other statistics that may also help you diagnose a particular problem. The more statistics ANTS MP collects, the longer it will take to collect statistics. So just turning everything on is probably a bad idea. But the option to selectively add in additional performance counters from the extensive list could be a very helpful thing for your memory profiling as it lets you see additional data that might provide clues about a particular problem that has been bothering you. ANTS MP integrates very nicely with all versions of Visual Studio that support plugins (i.e. all of the non-Express versions). Just note that if you choose “Profile Memory” from the “ANTS” menu that it will launch profiling for whichever project you have set as the Startup project. One quick tip from my experience so far using ANTS MP: if you want to properly understand your memory usage in an application you’ve written, first create an “empty” version of the type of project you are going to profile (a WPF application, an XNA game, etc.) and do a quick profiling session on that so that you know the baseline memory usage of the framework itself. By “empty” I mean just create a new project of that type in Visual Studio then compile it and run it with profiling – don’t do anything special or add in anything (except perhaps for any external libraries you’re planning to use). The first thing I tried ANTS MP out on was a demo XNA project of an editor that I’ve been working on for quite some time that involves a custom extension to XNA’s content pipeline. The first time I ran it and saw the unmanaged memory usage I was convinced I had some horrible bug that was creating extra copies of texture data (the demo project didn’t have a lot of texture data so when I saw a lot of unmanaged memory I instantly figured I was doing something wrong). Then I thought to run an empty project through and when I saw that the amount of unmanaged memory was virtually identical, it dawned on me that the CLR itself sits in unmanaged memory and that (thankfully) there was nothing wrong with my code! Quite a relief. Earlier, when discussing the overview video, I mentioned the API that lets you take snapshots from within your application. I gave it a quick trial and it’s very easy to integrate and make use of and is a really nice addition (especially for projects where you want to know what, if any, allocations there are in a specific, complicated section of code). The only concern I had was that if I hadn’t watched the overview video I might never have known it existed. Even then it took me five minutes of hunting around Red Gate’s website before I found the “Taking snapshots from your code" article that explains what DLL you need to add as a reference and what method of what class you should call in order to take an automatic snapshot (including the helpful warning to wrap it in a try-catch block since, under certain circumstances, it can raise an exception, such as trying to call it more than 5 times in 30 seconds. The difficulty in discovering and then finding information about the automatic snapshots API was one thing I thought could use improvement. Another thing I think would make it even better would be local copies of the webpages it links to. Although I’m generally always connected to the internet, I imagine there are more than a few developers who aren’t or who are behind very restrictive firewalls. For them (and for me, too, if my internet connection happens to be down), it would be nice to have those documents installed locally or to have the option to download an additional “documentation” package that would add local copies. Another thing that I wish could be easier to manage is the Filters area. Finding and setting individual filters is very easy as is understanding what those filter do. And breaking it up into three sections (basic, by object, and by reference) makes sense. But I could easily see myself running a long profiling session and forgetting that I had set some filter a long while earlier in a different filter section and then spending quite a bit of time trying to figure out why some problem that was clearly visible in the data wasn’t showing up in, e.g. the instance list before remembering to check all the filters for that one setting that was only culling a few things from view. Some sort of indicator icon next to the filter section names that appears you have at least one filter set in that area would be a nice visual clue to remind me that “oh yeah, I told it to only show objects on the Gen 2 heap! That’s why I’m not seeing those instances of the SuperMagic class!” Something that would be nice (but that Red Gate cannot really do anything about) would be if this could be used in Windows Phone 7 development. If Microsoft and Red Gate could work together to make this happen (even if just on the WP7 emulator), that would be amazing. Especially given the memory constraints that apps and games running on mobile devices need to work within, a good memory profiler would be a phenomenally helpful tool. If anyone at Microsoft reads this, it’d be really great if you could make something like that happen. Perhaps even a (subsidized) custom version just for WP7 development. (For XNA games, of course, you can create a Windows version of the game and use ANTS MP on the Windows version in order to get a better picture of your memory situation. For Silverlight on WP7, though, there’s quite a bit of educated guess work and WeakReference creation followed by forced collections in order to find the source of a memory problem.) The only other thing I found myself wanting was a “Back” button. Between my Windows Phone 7, Zune, and other things, I’ve grown very used to having a “back stack” that lets me just navigate back to where I came from. The ANTS MP interface is surprisingly easy to use given how much it lets you do, and once you start using it for any amount of time, you learn all of the different areas such that you know where to go. And it does remember the state of the areas you were previously in, of course. So if you go to, e.g., the Instance Retention Graph from the Class List and then return back to the Class List, it will remember which class you had selected and all that other state information. Still, a “Back” button would be a welcome addition to a future release. Bottom Line ANTS Memory Profiler is not an inexpensive tool. But my time is valuable. I can easily see ANTS MP saving me enough time tracking down memory problems to justify it on a cost basis. More importantly to me, knowing what is happening memory-wise in my programs and having the confidence that my code doesn’t have any hidden time bombs in it that will cause it to OOM if I leave it running for longer than I do when I spin it up real quickly for debugging or just to see how a new feature looks and feels is a good feeling. It’s a feeling that I like having and want to continue to have. I got the current version for free in order to review it. Having done so, I’ve now added it to my must-have tools and will gladly lay out the money for the next version when it comes out. It has a 14 day free trial, so if you aren’t sure if it’s right for you or if you think it seems interesting but aren’t really sure if it’s worth shelling out the money for it, give it a try.

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  • Ballooning Mac OS X kernel_task and Wired memory usage. How to diagnose / fix?

    - by user28930
    I have a very strange issue, which I'm having a hard time diagnosing as to the root cause. I have a Mac Pro (2008, 8-core 2.8 GHz, 8800GT) with 14 GB of RAM (recently upgraded because of this issue!). When I boot my system and log in, vm_stat / top / Activity Monitor will show that kernel_task has about 150 MB allocated, and the machine has about 800 MB of Wired memory being allocated. Even initially, 800 MB seems an awful lot of wired memory to be allocated with no applications running - but, it gets worse. (NB: Wired is locked, unswappable memory) After a very short time, sometimes triggered by something as simple as launching a terminal, kernel_task will balloon to 8-900 MB of Real Mem (RSIZE), and Wired Memory will accelerate to 1.6 GB (implying that all the extra memory requests are for wired RAM in the kernel). If I quit everything (I.E: no running applications, bar an activity monitor or terminal to view top), there is no appreciable reduction in either kernel_task RSIZE, or Wired Memory usage. Going the opposite way, and loading the system with tasks also shows that wired memory does not get reduced - and that importantly it is not reduced in preference to heavy swapping. If I log out and log back in again, it reduces a bit (450 MB kernel_task, 1.28 GB Wired), but not back to the start. I'm not running any wacky kexts - and futhermore, kextstat shows no huge memory allocations there; the largest being com.apple.nvidia.nv50hal at about 4 MB of Memory. The machine feels overall more sluggish when this has happened - unsurprisingly because such a huge amount of RAM has been marked as non-pageable. So I have a few questions: 1) Is there a good way to diagnose what has allocated all of this wired memory? It's often over 2 times the kernel_task size, running no applications. The real memory total doesn't seem to add up - it seems that there is a bunch of RAM that isn't being accounted for anywhere. 2) What is happening to cause the kernel to suddenly require 6 times as much memory?

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  • OS memory allocation addresses

    - by user1777914
    Quick curious question, memory allocation addresses are choosed by the language compiler or is it the OS which chooses the addresses for the memory asked? This is from a doubt about virtual memory, where it could be quickly explained as "let the process think he owns all the memory", but what happens on 64 bits architectures where only 48 bits are used for memory addresses if the process wants a higher address? Lets say you do a int a = malloc(sizeof(int)); and you have no memory left from the previous system call so you need to ask the OS for more memory, is the compiler the one who determines the memory address to allocate this variable, or does it just ask the OS for memory and it allocates it on the address returned by it?

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  • Linux bizarre memory report

    - by Igor Liner
    I took the following meminfo captures. I don't figure out how the free memory went from 8GB to almost 25GB, when only about 4GB of slab was freed. There was no change of the proccess memory consumption on time the meminfo output was taken. First meminfo with 8GB free memory: MemTotal: 66054256 kB MemFree: 8344960 kB Buffers: 1120 kB Cached: 30172312 kB SwapCached: 0 kB Active: 10795428 kB Inactive: 1914512 kB Active(anon): 10193124 kB Inactive(anon): 1441288 kB Active(file): 602304 kB Inactive(file): 473224 kB Unevictable: 26348912 kB Mlocked: 26348960 kB SwapTotal: 0 kB SwapFree: 0 kB Dirty: 0 kB Writeback: 0 kB AnonPages: 8886304 kB Mapped: 26383052 kB Shmem: 29097904 kB Slab: 6006384 kB SReclaimable: 3512404 kB SUnreclaim: 2493980 kB KernelStack: 15240 kB PageTables: 78724 kB NFS_Unstable: 0 kB Bounce: 0 kB WritebackTmp: 0 kB CommitLimit: 33027128 kB Committed_AS: 44446908 kB VmallocTotal: 34359738367 kB VmallocUsed: 426656 kB VmallocChunk: 34325375716 kB HardwareCorrupted: 0 kB AnonHugePages: 7696384 kB HugePages_Total: 0 HugePages_Free: 0 HugePages_Rsvd: 0 HugePages_Surp: 0 Hugepagesize: 2048 kB DirectMap4k: 6144 kB DirectMap2M: 2058240 kB DirectMap1G: 65011712 kB Second memory capture with almost 25GB free memory: MemTotal: 66054256 kB MemFree: 24949116 kB Buffers: 1120 kB Cached: 29085016 kB SwapCached: 0 kB Active: 10168904 kB Inactive: 1461156 kB Active(anon): 10168216 kB Inactive(anon): 1441956 kB Active(file): 688 kB Inactive(file): 19200 kB Unevictable: 26317328 kB Mlocked: 26317376 kB SwapTotal: 0 kB SwapFree: 0 kB Dirty: 0 kB Writeback: 0 kB AnonPages: 8861224 kB Mapped: 26351488 kB Shmem: 29066248 kB Slab: 1503440 kB SReclaimable: 232880 kB SUnreclaim: 1270560 kB KernelStack: 15256 kB PageTables: 79664 kB NFS_Unstable: 0 kB Bounce: 0 kB WritebackTmp: 0 kB CommitLimit: 33027128 kB Committed_AS: 44418280 kB VmallocTotal: 34359738367 kB VmallocUsed: 426656 kB VmallocChunk: 34325375716 kB HardwareCorrupted: 0 kB AnonHugePages: 7665664 kB HugePages_Total: 0 HugePages_Free: 0 HugePages_Rsvd: 0 HugePages_Surp: 0 Hugepagesize: 2048 kB DirectMap4k: 6144 kB DirectMap2M: 2058240 kB DirectMap1G: 65011712 kB

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