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  • PC3200 RAM in Older Computer?

    - by skaz
    Hello all, I am inheriting a Dell Dimension 8200, but it needs RAM to get up and running. I have PC3200 sticks lying around, but I am not sure how to go about figuring out if the RAM is compatible, as RAM has always confused me. Here is the Dell Dimension 8200 Tech Specs: http://support.dell.com/support/edocs/systems/dim8200/specs.htm For RAM, it says: Memory type PC800 (non-ECC) I don't know if that is just the kind that comes with it, and I can put in PC3200 (I think, if it worked, this would run at the lower rating? Is that true?), or if that means only PC800 is compatible. Any help would be appreciated.

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  • Lightest way to run Google Hangouts Chrome app on Mac

    - by jadengore
    I recently transitioned to Safari because I'm really tired of how Chrome hogs memory and drains my battery like crazy. The only thing that has been keeping the Chrome icon open is the Hangouts plugin. Basically, I am looking for the lightest way to run Hangouts on my Mac. By light, I mean the least amount of RAM usage, and preferably a way to do it without Chrome open/light version of Chrome that only opens extensions. Any suggestions? EDIT: Another thing I noticed was that Hangouts ignores your default browser if links are sent to you by chat, and when clicked they open in Chrome. My question doesn't relate to this at all, but I found it interesting...

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  • Can I extend my total RAM by buying more, and what kind do I need to buy

    - by Xeon06
    I currently have 4 GB total RAM and I would like to get some more, to bring it to a total of 8 GB. Is it possible to simply buy another 4 GB and bring it to 8? If so, what kind should I be buying? There is a lot of different possibilities, DDR3, DDR2, clock speed, etc. I am kind of lost among all this. My current setup goes like this: ACER EG43M mainboard Intel(R) Core(TM)2 Quad CPU Q8200 @ 2.33GHz 4 total RAM slots, 2 occupied by 2 GB sticks According to CPU-Z, my memory type is DDR3 (not sure how reliable that is) Full CPU-Z dump Windows 7 64-bit So basically, I want to know whether it's possible to extend my current RAM to get 8 GB total by buying another 4, and if so, what kind of RAM do I need? Note that I am not looking for shopping recommendations. I'm worried about the hardware compatibility.

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  • Understanding RAM usage on Linux

    - by stebbo
    I'm completely new to Linux and I'm just trying to understand where all my RAM is going. I've got a pretty fresh install of Xubuntu running as a VMWare guest, and I've given it 1.5GB RAM to play with. After only running two apps starting up Tomcat servers and also running Firefox, I've got hardly anything left. 160MB according to free -m. Looking at the output from Top, I see Java appearing twice, each stealing about 1/2 Gig resident memory. Both Tomcat instances use the same jdk, I would have thought I'd only see Java there once. What's the story? I had a screenshot but unfortunately couldn't post it being under 10 rep. Update The free -m output requested: total used free shared buffers cached Mem: 1419 1380 39 0 8 111 -/+ buffers/cache: 1259 160 Swap: 509 68 441 Top (coming)

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  • Windows 8 Task Manager RAM Usage Accuracy

    - by user264892
    The new Task Manager has a great UI in windows 8, however, there are some discrepancies in the data I can not account for: Machine: 8 GB of total ram. (This is a physical machine, not a virtual) The processes tab shows 45% of Memory utilized. The listed process do not add up to 3.5 GB of RAM, but instead add up to 0.948 GB. There is no "processes for all users" option. The performance Tab Shows: In use : 3.6 GB Available: 4.4 GB Committed : 4.1 /9.2 GB Cached: 3.7 GB Paged Pool: 376 MB Non-paged pool: 135 MB My reading of this says I have ALOT of "cloaked" processes running some where eating my ram. How do I interpret this data and how do I verify it?

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  • How to safely operate on parameters in threads, using C++ & Pthreads?

    - by ChrisCphDK
    Hi. I'm having some trouble with a program using pthreads, where occassional crashes occur, that could be related to how the threads operate on data So I have some basic questions about how to program using threads, and memory layout: Assume that a public class function performs some operations on some strings, and returns the result as a string. The prototype of the function could be like this: std::string SomeClass::somefunc(const std::string &strOne, const std::string &strTwo) { //Error checking of strings have been omitted std::string result = strOne.substr(0,5) + strTwo.substr(0,5); return result; } Is it correct to assume that strings, being dynamic, are stored on the heap, but that a reference to the string is allocated on the stack at runtime? Stack: [Some mem addr] pointer address to where the string is on the heap Heap: [Some mem addr] memory allocated for the initial string which may grow or shrink To make the function thread safe, the function is extended with the following mutex (which is declared as private in the "SomeClass") locking: std::string SomeClass::somefunc(const std::string &strOne, const std::string &strTwo) { pthread_mutex_lock(&someclasslock); //Error checking of strings have been omitted std::string result = strOne.substr(0,5) + strTwo.substr(0,5); pthread_mutex_unlock(&someclasslock); return result; } Is this a safe way of locking down the operations being done on the strings (all three), or could a thread be stopped by the scheduler in the following cases, which I'd assume would mess up the intended logic: a. Right after the function is called, and the parameters: strOne & strTwo have been set in the two reference pointers that the function has on the stack, the scheduler takes away processing time for the thread and lets a new thread in, which overwrites the reference pointers to the function, which then again gets stopped by the scheduler, letting the first thread back in? b. Can the same occur with the "result" string: the first string builds the result, unlocks the mutex, but before returning the scheduler lets in another thread which performs all of it's work, overwriting the result etc. Or are the reference parameters / result string being pushed onto the stack while another thread is doing performing it's task? Is the safe / correct way of doing this in threads, and "returning" a result, to pass a reference to a string that will be filled with the result instead: void SomeClass::somefunc(const std::string &strOne, const std::string &strTwo, std::string result) { pthread_mutex_lock(&someclasslock); //Error checking of strings have been omitted result = strOne.substr(0,5) + strTwo.substr(0,5); pthread_mutex_unlock(&someclasslock); } The intended logic is that several objects of the "SomeClass" class creates new threads and passes objects of themselves as parameters, and then calls the function: "someFunc": int SomeClass::startNewThread() { pthread_attr_t attr; pthread_t pThreadID; if(pthread_attr_init(&attr) != 0) return -1; if(pthread_attr_setdetachstate(&attr, PTHREAD_CREATE_DETACHED) != 0) return -2; if(pthread_create(&pThreadID, &attr, proxyThreadFunc, this) != 0) return -3; if(pthread_attr_destroy(&attr) != 0) return -4; return 0; } void* proxyThreadFunc(void* someClassObjPtr) { return static_cast<SomeClass*> (someClassObjPtr)->somefunc("long string","long string"); } Sorry for the long description. But I hope the questions and intended purpose is clear, if not let me know and I'll elaborate. Best regards. Chris

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  • High Linux loads on low CPU/memory usage

    - by user13323
    Hi. I have quite strange situation, where my CentOS 5.5 box loads are high, but the CPU and memory used are pretty low: top - 20:41:38 up 42 days, 6:14, 2 users, load average: 19.79, 21.25, 18.87 Tasks: 254 total, 1 running, 253 sleeping, 0 stopped, 0 zombie Cpu(s): 3.8%us, 0.3%sy, 0.1%ni, 95.0%id, 0.6%wa, 0.0%hi, 0.1%si, 0.0%st Mem: 4035284k total, 4008084k used, 27200k free, 38748k buffers Swap: 4208928k total, 242576k used, 3966352k free, 1465008k cached free -mt total used free shared buffers cached Mem: 3940 3910 29 0 37 1427 -/+ buffers/cache: 2445 1495 Swap: 4110 236 3873 Total: 8050 4147 3903 Iostat also shows good results: avg-cpu: %user %nice %system %iowait %steal %idle 3.83 0.13 0.41 0.58 0.00 95.05 Here is the ps aux output: USER PID %CPU %MEM VSZ RSS TTY STAT START TIME COMMAND root 1 0.0 0.0 10348 80 ? Ss 2010 2:11 init [3] root 2 0.0 0.0 0 0 ? S< 2010 0:00 [migration/0] root 3 0.0 0.0 0 0 ? SN 2010 0:00 [ksoftirqd/0] root 4 0.0 0.0 0 0 ? S< 2010 0:00 [watchdog/0] root 5 0.0 0.0 0 0 ? S< 2010 0:02 [migration/1] root 6 0.0 0.0 0 0 ? SN 2010 0:00 [ksoftirqd/1] root 7 0.0 0.0 0 0 ? S< 2010 0:00 [watchdog/1] root 8 0.0 0.0 0 0 ? S< 2010 0:02 [migration/2] root 9 0.0 0.0 0 0 ? SN 2010 0:00 [ksoftirqd/2] root 10 0.0 0.0 0 0 ? S< 2010 0:00 [watchdog/2] root 11 0.0 0.0 0 0 ? S< 2010 0:02 [migration/3] root 12 0.0 0.0 0 0 ? SN 2010 0:00 [ksoftirqd/3] root 13 0.0 0.0 0 0 ? S< 2010 0:00 [watchdog/3] root 14 0.0 0.0 0 0 ? S< 2010 0:03 [migration/4] root 15 0.0 0.0 0 0 ? SN 2010 0:00 [ksoftirqd/4] root 16 0.0 0.0 0 0 ? S< 2010 0:00 [watchdog/4] root 17 0.0 0.0 0 0 ? S< 2010 0:01 [migration/5] root 18 0.0 0.0 0 0 ? SN 2010 0:00 [ksoftirqd/5] root 19 0.0 0.0 0 0 ? S< 2010 0:00 [watchdog/5] root 20 0.0 0.0 0 0 ? S< 2010 0:11 [migration/6] root 21 0.0 0.0 0 0 ? SN 2010 0:00 [ksoftirqd/6] root 22 0.0 0.0 0 0 ? S< 2010 0:00 [watchdog/6] root 23 0.0 0.0 0 0 ? S< 2010 0:01 [migration/7] root 24 0.0 0.0 0 0 ? SN 2010 0:00 [ksoftirqd/7] root 25 0.0 0.0 0 0 ? S< 2010 0:00 [watchdog/7] root 26 0.0 0.0 0 0 ? S< 2010 0:00 [migration/8] root 27 0.0 0.0 0 0 ? SN 2010 0:00 [ksoftirqd/8] root 28 0.0 0.0 0 0 ? S< 2010 0:00 [watchdog/8] root 29 0.0 0.0 0 0 ? S< 2010 0:00 [migration/9] root 30 0.0 0.0 0 0 ? SN 2010 0:00 [ksoftirqd/9] root 31 0.0 0.0 0 0 ? S< 2010 0:00 [watchdog/9] root 32 0.0 0.0 0 0 ? S< 2010 0:08 [migration/10] root 33 0.0 0.0 0 0 ? SN 2010 0:00 [ksoftirqd/10] root 34 0.0 0.0 0 0 ? S< 2010 0:00 [watchdog/10] root 35 0.0 0.0 0 0 ? S< 2010 0:05 [migration/11] root 36 0.0 0.0 0 0 ? SN 2010 0:00 [ksoftirqd/11] root 37 0.0 0.0 0 0 ? S< 2010 0:00 [watchdog/11] root 38 0.0 0.0 0 0 ? S< 2010 0:02 [migration/12] root 39 0.0 0.0 0 0 ? SN 2010 0:00 [ksoftirqd/12] root 40 0.0 0.0 0 0 ? S< 2010 0:00 [watchdog/12] root 41 0.0 0.0 0 0 ? S< 2010 0:14 [migration/13] root 42 0.0 0.0 0 0 ? SN 2010 0:00 [ksoftirqd/13] root 43 0.0 0.0 0 0 ? S< 2010 0:00 [watchdog/13] root 44 0.0 0.0 0 0 ? S< 2010 0:04 [migration/14] root 45 0.0 0.0 0 0 ? SN 2010 0:00 [ksoftirqd/14] root 46 0.0 0.0 0 0 ? S< 2010 0:00 [watchdog/14] root 47 0.0 0.0 0 0 ? S< 2010 0:01 [migration/15] root 48 0.0 0.0 0 0 ? SN 2010 0:00 [ksoftirqd/15] root 49 0.0 0.0 0 0 ? S< 2010 0:00 [watchdog/15] root 50 0.0 0.0 0 0 ? S< 2010 0:00 [events/0] root 51 0.0 0.0 0 0 ? S< 2010 0:00 [events/1] root 52 0.0 0.0 0 0 ? S< 2010 0:00 [events/2] root 53 0.0 0.0 0 0 ? S< 2010 0:00 [events/3] root 54 0.0 0.0 0 0 ? S< 2010 0:00 [events/4] root 55 0.0 0.0 0 0 ? S< 2010 0:00 [events/5] root 56 0.0 0.0 0 0 ? S< 2010 0:00 [events/6] root 57 0.0 0.0 0 0 ? S< 2010 0:00 [events/7] root 58 0.0 0.0 0 0 ? S< 2010 0:00 [events/8] root 59 0.0 0.0 0 0 ? S< 2010 0:00 [events/9] root 60 0.0 0.0 0 0 ? S< 2010 0:00 [events/10] root 61 0.0 0.0 0 0 ? S< 2010 0:00 [events/11] root 62 0.0 0.0 0 0 ? S< 2010 0:00 [events/12] root 63 0.0 0.0 0 0 ? S< 2010 0:00 [events/13] root 64 0.0 0.0 0 0 ? S< 2010 0:00 [events/14] root 65 0.0 0.0 0 0 ? S< 2010 0:00 [events/15] root 66 0.0 0.0 0 0 ? S< 2010 0:00 [khelper] root 107 0.0 0.0 0 0 ? S< 2010 0:00 [kthread] root 126 0.0 0.0 0 0 ? S< 2010 0:00 [kblockd/0] root 127 0.0 0.0 0 0 ? S< 2010 0:03 [kblockd/1] root 128 0.0 0.0 0 0 ? S< 2010 0:01 [kblockd/2] root 129 0.0 0.0 0 0 ? S< 2010 0:00 [kblockd/3] root 130 0.0 0.0 0 0 ? S< 2010 0:05 [kblockd/4] root 131 0.0 0.0 0 0 ? S< 2010 0:00 [kblockd/5] root 132 0.0 0.0 0 0 ? S< 2010 0:00 [kblockd/6] root 133 0.0 0.0 0 0 ? S< 2010 0:00 [kblockd/7] root 134 0.0 0.0 0 0 ? S< 2010 0:00 [kblockd/8] root 135 0.0 0.0 0 0 ? S< 2010 0:02 [kblockd/9] root 136 0.0 0.0 0 0 ? S< 2010 0:00 [kblockd/10] root 137 0.0 0.0 0 0 ? S< 2010 0:00 [kblockd/11] root 138 0.0 0.0 0 0 ? S< 2010 0:04 [kblockd/12] root 139 0.0 0.0 0 0 ? S< 2010 0:00 [kblockd/13] root 140 0.0 0.0 0 0 ? S< 2010 0:00 [kblockd/14] root 141 0.0 0.0 0 0 ? S< 2010 0:00 [kblockd/15] root 142 0.0 0.0 0 0 ? S< 2010 0:00 [kacpid] root 281 0.0 0.0 0 0 ? S< 2010 0:00 [cqueue/0] root 282 0.0 0.0 0 0 ? S< 2010 0:00 [cqueue/1] root 283 0.0 0.0 0 0 ? S< 2010 0:00 [cqueue/2] root 284 0.0 0.0 0 0 ? S< 2010 0:00 [cqueue/3] root 285 0.0 0.0 0 0 ? S< 2010 0:00 [cqueue/4] root 286 0.0 0.0 0 0 ? S< 2010 0:00 [cqueue/5] root 287 0.0 0.0 0 0 ? S< 2010 0:00 [cqueue/6] root 288 0.0 0.0 0 0 ? S< 2010 0:00 [cqueue/7] root 289 0.0 0.0 0 0 ? S< 2010 0:00 [cqueue/8] root 290 0.0 0.0 0 0 ? S< 2010 0:00 [cqueue/9] root 291 0.0 0.0 0 0 ? S< 2010 0:00 [cqueue/10] root 292 0.0 0.0 0 0 ? S< 2010 0:00 [cqueue/11] root 293 0.0 0.0 0 0 ? S< 2010 0:00 [cqueue/12] root 294 0.0 0.0 0 0 ? S< 2010 0:00 [cqueue/13] root 295 0.0 0.0 0 0 ? S< 2010 0:00 [cqueue/14] root 296 0.0 0.0 0 0 ? S< 2010 0:00 [cqueue/15] root 299 0.0 0.0 0 0 ? S< 2010 0:00 [khubd] root 301 0.0 0.0 0 0 ? S< 2010 0:00 [kseriod] root 490 0.0 0.0 0 0 ? S 2010 0:00 [khungtaskd] root 493 0.1 0.0 0 0 ? S< 2010 94:48 [kswapd1] root 494 0.0 0.0 0 0 ? S< 2010 0:00 [aio/0] root 495 0.0 0.0 0 0 ? S< 2010 0:00 [aio/1] root 496 0.0 0.0 0 0 ? S< 2010 0:00 [aio/2] root 497 0.0 0.0 0 0 ? S< 2010 0:00 [aio/3] root 498 0.0 0.0 0 0 ? S< 2010 0:00 [aio/4] root 499 0.0 0.0 0 0 ? S< 2010 0:00 [aio/5] root 500 0.0 0.0 0 0 ? S< 2010 0:00 [aio/6] root 501 0.0 0.0 0 0 ? S< 2010 0:00 [aio/7] root 502 0.0 0.0 0 0 ? S< 2010 0:00 [aio/8] root 503 0.0 0.0 0 0 ? S< 2010 0:00 [aio/9] root 504 0.0 0.0 0 0 ? S< 2010 0:00 [aio/10] root 505 0.0 0.0 0 0 ? S< 2010 0:00 [aio/11] root 506 0.0 0.0 0 0 ? S< 2010 0:00 [aio/12] root 507 0.0 0.0 0 0 ? S< 2010 0:00 [aio/13] root 508 0.0 0.0 0 0 ? S< 2010 0:00 [aio/14] root 509 0.0 0.0 0 0 ? S< 2010 0:00 [aio/15] root 665 0.0 0.0 0 0 ? S< 2010 0:00 [kpsmoused] root 808 0.0 0.0 0 0 ? S< 2010 0:00 [ata/0] root 809 0.0 0.0 0 0 ? S< 2010 0:00 [ata/1] root 810 0.0 0.0 0 0 ? S< 2010 0:00 [ata/2] root 811 0.0 0.0 0 0 ? S< 2010 0:00 [ata/3] root 812 0.0 0.0 0 0 ? S< 2010 0:00 [ata/4] root 813 0.0 0.0 0 0 ? S< 2010 0:00 [ata/5] root 814 0.0 0.0 0 0 ? S< 2010 0:00 [ata/6] root 815 0.0 0.0 0 0 ? S< 2010 0:00 [ata/7] root 816 0.0 0.0 0 0 ? S< 2010 0:00 [ata/8] root 817 0.0 0.0 0 0 ? S< 2010 0:00 [ata/9] root 818 0.0 0.0 0 0 ? S< 2010 0:00 [ata/10] root 819 0.0 0.0 0 0 ? S< 2010 0:00 [ata/11] root 820 0.0 0.0 0 0 ? S< 2010 0:00 [ata/12] root 821 0.0 0.0 0 0 ? S< 2010 0:00 [ata/13] root 822 0.0 0.0 0 0 ? S< 2010 0:00 [ata/14] root 823 0.0 0.0 0 0 ? S< 2010 0:00 [ata/15] root 824 0.0 0.0 0 0 ? S< 2010 0:00 [ata_aux] root 842 0.0 0.0 0 0 ? S< 2010 0:00 [scsi_eh_0] root 843 0.0 0.0 0 0 ? S< 2010 0:00 [scsi_eh_1] root 844 0.0 0.0 0 0 ? S< 2010 0:00 [scsi_eh_2] root 845 0.0 0.0 0 0 ? S< 2010 0:00 [scsi_eh_3] root 846 0.0 0.0 0 0 ? S< 2010 0:00 [scsi_eh_4] root 847 0.0 0.0 0 0 ? S< 2010 0:00 [scsi_eh_5] root 882 0.0 0.0 0 0 ? S< 2010 0:00 [kstriped] root 951 0.0 0.0 0 0 ? S< 2010 4:24 [kjournald] root 976 0.0 0.0 0 0 ? S< 2010 0:00 [kauditd] postfix 990 0.0 0.0 54208 2284 ? S 21:19 0:00 pickup -l -t fifo -u root 1013 0.0 0.0 12676 8 ? S<s 2010 0:00 /sbin/udevd -d root 1326 0.0 0.0 90900 3400 ? Ss 14:53 0:00 sshd: root@notty root 1410 0.0 0.0 53972 2108 ? Ss 14:53 0:00 /usr/libexec/openssh/sftp-server root 2690 0.0 0.0 0 0 ? S< 2010 0:00 [kmpathd/0] root 2691 0.0 0.0 0 0 ? S< 2010 0:00 [kmpathd/1] root 2692 0.0 0.0 0 0 ? S< 2010 0:00 [kmpathd/2] root 2693 0.0 0.0 0 0 ? S< 2010 0:00 [kmpathd/3] root 2694 0.0 0.0 0 0 ? S< 2010 0:00 [kmpathd/4] root 2695 0.0 0.0 0 0 ? S< 2010 0:00 [kmpathd/5] root 2696 0.0 0.0 0 0 ? S< 2010 0:00 [kmpathd/6] root 2697 0.0 0.0 0 0 ? S< 2010 0:00 [kmpathd/7] root 2698 0.0 0.0 0 0 ? S< 2010 0:00 [kmpathd/8] root 2699 0.0 0.0 0 0 ? S< 2010 0:00 [kmpathd/9] root 2700 0.0 0.0 0 0 ? S< 2010 0:00 [kmpathd/10] root 2701 0.0 0.0 0 0 ? S< 2010 0:00 [kmpathd/11] root 2702 0.0 0.0 0 0 ? S< 2010 0:00 [kmpathd/12] root 2703 0.0 0.0 0 0 ? S< 2010 0:00 [kmpathd/13] root 2704 0.0 0.0 0 0 ? S< 2010 0:00 [kmpathd/14] root 2705 0.0 0.0 0 0 ? S< 2010 0:00 [kmpathd/15] root 2706 0.0 0.0 0 0 ? S< 2010 0:00 [kmpath_handlerd] root 2755 0.0 0.0 0 0 ? S< 2010 4:35 [kjournald] root 2757 0.0 0.0 0 0 ? S< 2010 3:38 [kjournald] root 2759 0.0 0.0 0 0 ? S< 2010 4:10 [kjournald] root 2761 0.0 0.0 0 0 ? S< 2010 4:26 [kjournald] root 2763 0.0 0.0 0 0 ? S< 2010 3:15 [kjournald] root 2765 0.0 0.0 0 0 ? S< 2010 3:04 [kjournald] root 2767 0.0 0.0 0 0 ? S< 2010 3:02 [kjournald] root 2769 0.0 0.0 0 0 ? S< 2010 2:58 [kjournald] root 2771 0.0 0.0 0 0 ? S< 2010 0:00 [kjournald] root 3340 0.0 0.0 5908 356 ? Ss 2010 2:48 syslogd -m 0 root 3343 0.0 0.0 3804 212 ? Ss 2010 0:03 klogd -x root 3430 0.0 0.0 0 0 ? S< 2010 0:50 [kondemand/0] root 3431 0.0 0.0 0 0 ? S< 2010 0:54 [kondemand/1] root 3432 0.0 0.0 0 0 ? S< 2010 0:00 [kondemand/2] root 3433 0.0 0.0 0 0 ? S< 2010 0:00 [kondemand/3] root 3434 0.0 0.0 0 0 ? S< 2010 0:00 [kondemand/4] root 3435 0.0 0.0 0 0 ? S< 2010 0:00 [kondemand/5] root 3436 0.0 0.0 0 0 ? S< 2010 0:00 [kondemand/6] root 3437 0.0 0.0 0 0 ? S< 2010 0:00 [kondemand/7] root 3438 0.0 0.0 0 0 ? S< 2010 0:00 [kondemand/8] root 3439 0.0 0.0 0 0 ? S< 2010 0:00 [kondemand/9] root 3440 0.0 0.0 0 0 ? S< 2010 0:00 [kondemand/10] root 3441 0.0 0.0 0 0 ? S< 2010 0:00 [kondemand/11] root 3442 0.0 0.0 0 0 ? S< 2010 0:00 [kondemand/12] root 3443 0.0 0.0 0 0 ? S< 2010 0:00 [kondemand/13] root 3444 0.0 0.0 0 0 ? S< 2010 0:00 [kondemand/14] root 3445 0.0 0.0 0 0 ? S< 2010 0:00 [kondemand/15] root 3461 0.0 0.0 10760 284 ? Ss 2010 3:44 irqbalance rpc 3481 0.0 0.0 8052 4 ? Ss 2010 0:00 portmap root 3526 0.0 0.0 0 0 ? S< 2010 0:00 [rpciod/0] root 3527 0.0 0.0 0 0 ? S< 2010 0:00 [rpciod/1] root 3528 0.0 0.0 0 0 ? S< 2010 0:00 [rpciod/2] root 3529 0.0 0.0 0 0 ? S< 2010 0:00 [rpciod/3] root 3530 0.0 0.0 0 0 ? S< 2010 0:00 [rpciod/4] root 3531 0.0 0.0 0 0 ? S< 2010 0:00 [rpciod/5] root 3532 0.0 0.0 0 0 ? S< 2010 0:00 [rpciod/6] root 3533 0.0 0.0 0 0 ? S< 2010 0:00 [rpciod/7] root 3534 0.0 0.0 0 0 ? S< 2010 0:00 [rpciod/8] root 3535 0.0 0.0 0 0 ? S< 2010 0:00 [rpciod/9] root 3536 0.0 0.0 0 0 ? S< 2010 0:00 [rpciod/10] root 3537 0.0 0.0 0 0 ? S< 2010 0:00 [rpciod/11] root 3538 0.0 0.0 0 0 ? S< 2010 0:00 [rpciod/12] root 3539 0.0 0.0 0 0 ? S< 2010 0:00 [rpciod/13] root 3540 0.0 0.0 0 0 ? S< 2010 0:00 [rpciod/14] root 3541 0.0 0.0 0 0 ? S< 2010 0:00 [rpciod/15] root 3563 0.0 0.0 10160 8 ? Ss 2010 0:00 rpc.statd root 3595 0.0 0.0 55180 4 ? Ss 2010 0:00 rpc.idmapd dbus 3618 0.0 0.0 21256 28 ? Ss 2010 0:00 dbus-daemon --system root 3649 0.2 0.4 563084 18796 ? S<sl 2010 179:03 mfsmount /mnt/mfs -o rw,mfsmaster=web1.ovs.local root 3702 0.0 0.0 3800 8 ? Ss 2010 0:00 /usr/sbin/acpid 68 3715 0.0 0.0 31312 816 ? Ss 2010 3:14 hald root 3716 0.0 0.0 21692 28 ? S 2010 0:00 hald-runner 68 3726 0.0 0.0 12324 8 ? S 2010 0:00 hald-addon-acpi: listening on acpid socket /var/run/acpid.socket 68 3730 0.0 0.0 12324 8 ? S 2010 0:00 hald-addon-keyboard: listening on /dev/input/event0 root 3773 0.0 0.0 62608 332 ? Ss 2010 0:00 /usr/sbin/sshd ganglia 3786 0.0 0.0 24704 988 ? Ss 2010 14:26 /usr/sbin/gmond root 3843 0.0 0.0 54144 300 ? Ss 2010 1:49 /usr/libexec/postfix/master postfix 3855 0.0 0.0 54860 1060 ? S 2010 0:22 qmgr -l -t fifo -u root 3877 0.0 0.0 74828 708 ? Ss 2010 1:15 crond root 3891 1.4 1.9 326960 77704 ? S<l 2010 896:59 mfschunkserver root 4122 0.0 0.0 18732 176 ? Ss 2010 0:10 /usr/sbin/atd root 4193 0.0 0.8 129180 35984 ? Ssl 2010 11:04 /usr/bin/ruby /usr/sbin/puppetd root 4223 0.0 0.0 18416 172 ? S 2010 0:10 /usr/sbin/smartd -q never root 4227 0.0 0.0 3792 8 tty1 Ss+ 2010 0:00 /sbin/mingetty tty1 root 4230 0.0 0.0 3792 8 tty2 Ss+ 2010 0:00 /sbin/mingetty tty2 root 4231 0.0 0.0 3792 8 tty3 Ss+ 2010 0:00 /sbin/mingetty tty3 root 4233 0.0 0.0 3792 8 tty4 Ss+ 2010 0:00 /sbin/mingetty tty4 root 4234 0.0 0.0 3792 8 tty5 Ss+ 2010 0:00 /sbin/mingetty tty5 root 4236 0.0 0.0 3792 8 tty6 Ss+ 2010 0:00 /sbin/mingetty tty6 root 5596 0.0 0.0 19368 20 ? Ss 2010 0:00 DarwinStreamingServer qtss 5597 0.8 0.9 166572 37408 ? Sl 2010 523:02 DarwinStreamingServer root 8714 0.0 0.0 0 0 ? S Jan31 0:33 [pdflush] root 9914 0.0 0.0 65612 968 pts/1 R+ 21:49 0:00 ps aux root 10765 0.0 0.0 76792 1080 ? Ss Jan24 0:58 SCREEN root 10766 0.0 0.0 66212 872 pts/3 Ss Jan24 0:00 /bin/bash root 11833 0.0 0.0 63852 1060 pts/3 S+ 17:17 0:00 /bin/sh ./launch.sh root 11834 437 42.9 4126884 1733348 pts/3 Sl+ 17:17 1190:50 /usr/bin/java -Xms128m -Xmx512m -XX:+UseConcMarkSweepGC -jar /JavaCore/JavaCore.jar root 13127 4.7 1.1 110564 46876 ? Ssl 17:18 12:55 /JavaCore/fetcher.bin root 19392 0.0 0.0 90108 3336 ? Rs 20:35 0:00 sshd: root@pts/1 root 19401 0.0 0.0 66216 1640 pts/1 Ss 20:35 0:00 -bash root 20567 0.0 0.0 90108 412 ? Ss Jan16 1:58 sshd: root@pts/0 root 20569 0.0 0.0 66084 912 pts/0 Ss Jan16 0:00 -bash root 21053 0.0 0.0 63856 28 ? S Jan30 0:00 /bin/sh /usr/bin/WowzaMediaServerd /usr/local/WowzaMediaServer/bin/setenv.sh /var/run/WowzaM root 21054 2.9 10.3 2252652 418468 ? Sl Jan30 314:25 java -Xmx1200M -server -Djava.net.preferIPv4Stack=true -Dcom.sun.management.jmxremote=true - root 21915 0.0 0.0 0 0 ? S Feb01 0:00 [pdflush] root 29996 0.0 0.0 76524 1004 pts/0 S+ 14:41 0:00 screen -x Any idea what could this be, or where I should look for more diagnostic information? Thanks.

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  • Memory leak / GLib issue.

    - by Andrei Ciobanu
    1: /* 2: * File: xyn-playlist.c 3: * Author: Andrei Ciobanu 4: * 5: * Created on June 4, 2010, 12:47 PM 6: */ 7:   8: #include <dirent.h> 9: #include <glib.h> 10: #include <stdio.h> 11: #include <stdlib.h> 12: #include <sys/stat.h> 13: #include <unistd.h> 14:   15: /** 16: * Returns a list all the file(paths) from a directory. 17: * Returns 'NULL' if a certain error occurs. 18: * @param dir_path. 19: * @param A list of gchars* indicating what file patterns to detect. 20: */ 21: GSList *xyn_pl_get_files(const gchar *dir_path, GSList *file_patterns) { 22: /* Returning list containing file paths */ 23: GSList *fpaths = NULL; 24: /* Used to scan directories for subdirs. Acts like a 25: * stack, to avoid recursion. */ 26: GSList *dirs = NULL; 27: /* Current dir */ 28: DIR *cdir = NULL; 29: /* Current dir entries */ 30: struct dirent *cent = NULL; 31: /* File stats */ 32: struct stat cent_stat; 33: /* dir_path duplicate, on the heap */ 34: gchar *dir_pdup; 35:   36: if (dir_path == NULL) { 37: return NULL; 38: } 39:   40: dir_pdup = g_strdup((const gchar*) dir_path); 41: dirs = g_slist_append(dirs, (gpointer) dir_pdup); 42: while (dirs != NULL) { 43: cdir = opendir((const gchar*) dirs->data); 44: if (cdir == NULL) { 45: g_slist_free(dirs); 46: g_slist_free(fpaths); 47: return NULL; 48: } 49: chdir((const gchar*) dirs->data); 50: while ((cent = readdir(cdir)) != NULL) { 51: lstat(cent->d_name, &cent_stat); 52: if (S_ISDIR(cent_stat.st_mode)) { 53: if (g_strcmp0(cent->d_name, ".") == 0 || 54: g_strcmp0(cent->d_name, "..") == 0) { 55: /* Skip "." and ".." dirs */ 56: continue; 57: } 58: dirs = g_slist_append(dirs, 59: g_strconcat((gchar*) dirs->data, "/", cent->d_name, NULL)); 60: } else { 61: fpaths = g_slist_append(fpaths, 62: g_strconcat((gchar*) dirs->data, "/", cent->d_name, NULL)); 63: } 64: } 65: g_free(dirs->data); 66: dirs = g_slist_delete_link(dirs, dirs); 67: closedir(cdir); 68: } 69: return fpaths; 70: } 71:   72: int main(int argc, char** argv) { 73: GSList *l = NULL; 74: l = xyn_pl_get_files("/home/andrei/Music", NULL); 75: g_slist_foreach(l,(GFunc)printf,NULL); 76: printf("%d\n",g_slist_length(l)); 77: g_slist_free(l); 78: return (0); 79: } 80:   81:   82: -----------------------------------------------------------------------------------------------==15429== 83: ==15429== HEAP SUMMARY: 84: ==15429== in use at exit: 751,451 bytes in 7,263 blocks 85: ==15429== total heap usage: 8,611 allocs, 1,348 frees, 22,898,217 bytes allocated 86: ==15429== 87: ==15429== 120 bytes in 1 blocks are possibly lost in loss record 1 of 11 88: ==15429== at 0x4024106: memalign (vg_replace_malloc.c:581) 89: ==15429== by 0x4024163: posix_memalign (vg_replace_malloc.c:709) 90: ==15429== by 0x40969C1: ??? (in /lib/libglib-2.0.so.0.2400.1) 91: ==15429== by 0x40971F6: g_slice_alloc (in /lib/libglib-2.0.so.0.2400.1) 92: ==15429== by 0x40988A5: g_slist_append (in /lib/libglib-2.0.so.0.2400.1) 93: ==15429== by 0x80488F0: xyn_pl_get_files (xyn-playlist.c:41) 94: ==15429== by 0x8048848: main (main.c:18) 95: ==15429== 96: ==15429== 129 bytes in 1 blocks are possibly lost in loss record 2 of 11 97: ==15429== at 0x4024F20: malloc (vg_replace_malloc.c:236) 98: ==15429== by 0x4081243: g_malloc (in /lib/libglib-2.0.so.0.2400.1) 99: ==15429== by 0x409B85B: g_strconcat (in /lib/libglib-2.0.so.0.2400.1) 100: ==15429== by 0x80489FE: xyn_pl_get_files (xyn-playlist.c:62) 101: ==15429== by 0x8048848: main (main.c:18) 102: ==15429== 103: ==15429== 360 bytes in 3 blocks are possibly lost in loss record 3 of 11 104: ==15429== at 0x4024106: memalign (vg_replace_malloc.c:581) 105: ==15429== by 0x4024163: posix_memalign (vg_replace_malloc.c:709) 106: ==15429== by 0x40969C1: ??? (in /lib/libglib-2.0.so.0.2400.1) 107: ==15429== by 0x4097222: g_slice_alloc (in /lib/libglib-2.0.so.0.2400.1) 108: ==15429== by 0x40988A5: g_slist_append (in /lib/libglib-2.0.so.0.2400.1) 109: ==15429== by 0x80488F0: xyn_pl_get_files (xyn-playlist.c:41) 110: ==15429== by 0x8048848: main (main.c:18) 111: ==15429== 112: ==15429== 508 bytes in 1 blocks are still reachable in loss record 4 of 11 113: ==15429== at 0x402425F: calloc (vg_replace_malloc.c:467) 114: ==15429== by 0x408113B: g_malloc0 (in /lib/libglib-2.0.so.0.2400.1) 115: ==15429== by 0x409624D: ??? (in /lib/libglib-2.0.so.0.2400.1) 116: ==15429== by 0x409710C: g_slice_alloc (in /lib/libglib-2.0.so.0.2400.1) 117: ==15429== by 0x40988A5: g_slist_append (in /lib/libglib-2.0.so.0.2400.1) 118: ==15429== by 0x80488F0: xyn_pl_get_files (xyn-playlist.c:41) 119: ==15429== by 0x8048848: main (main.c:18) 120: ==15429== 121: ==15429== 508 bytes in 1 blocks are still reachable in loss record 5 of 11 122: ==15429== at 0x402425F: calloc (vg_replace_malloc.c:467) 123: ==15429== by 0x408113B: g_malloc0 (in /lib/libglib-2.0.so.0.2400.1) 124: ==15429== by 0x409626F: ??? (in /lib/libglib-2.0.so.0.2400.1) 125: ==15429== by 0x409710C: g_slice_alloc (in /lib/libglib-2.0.so.0.2400.1) 126: ==15429== by 0x40988A5: g_slist_append (in /lib/libglib-2.0.so.0.2400.1) 127: ==15429== by 0x80488F0: xyn_pl_get_files (xyn-playlist.c:41) 128: ==15429== by 0x8048848: main (main.c:18) 129: ==15429== 130: ==15429== 508 bytes in 1 blocks are still reachable in loss record 6 of 11 131: ==15429== at 0x402425F: calloc (vg_replace_malloc.c:467) 132: ==15429== by 0x408113B: g_malloc0 (in /lib/libglib-2.0.so.0.2400.1) 133: ==15429== by 0x4096291: ??? (in /lib/libglib-2.0.so.0.2400.1) 134: ==15429== by 0x409710C: g_slice_alloc (in /lib/libglib-2.0.so.0.2400.1) 135: ==15429== by 0x40988A5: g_slist_append (in /lib/libglib-2.0.so.0.2400.1) 136: ==15429== by 0x80488F0: xyn_pl_get_files (xyn-playlist.c:41) 137: ==15429== by 0x8048848: main (main.c:18) 138: ==15429== 139: ==15429== 1,200 bytes in 10 blocks are possibly lost in loss record 7 of 11 140: ==15429== at 0x4024106: memalign (vg_replace_malloc.c:581) 141: ==15429== by 0x4024163: posix_memalign (vg_replace_malloc.c:709) 142: ==15429== by 0x40969C1: ??? (in /lib/libglib-2.0.so.0.2400.1) 143: ==15429== by 0x40971F6: g_slice_alloc (in /lib/libglib-2.0.so.0.2400.1) 144: ==15429== by 0x40988A5: g_slist_append (in /lib/libglib-2.0.so.0.2400.1) 145: ==15429== by 0x8048A0D: xyn_pl_get_files (xyn-playlist.c:61) 146: ==15429== by 0x8048848: main (main.c:18) 147: ==15429== 148: ==15429== 2,040 bytes in 1 blocks are still reachable in loss record 8 of 11 149: ==15429== at 0x402425F: calloc (vg_replace_malloc.c:467) 150: ==15429== by 0x408113B: g_malloc0 (in /lib/libglib-2.0.so.0.2400.1) 151: ==15429== by 0x40970AB: g_slice_alloc (in /lib/libglib-2.0.so.0.2400.1) 152: ==15429== by 0x40988A5: g_slist_append (in /lib/libglib-2.0.so.0.2400.1) 153: ==15429== by 0x80488F0: xyn_pl_get_files (xyn-playlist.c:41) 154: ==15429== by 0x8048848: main (main.c:18) 155: ==15429== 156: ==15429== 4,320 bytes in 36 blocks are possibly lost in loss record 9 of 11 157: ==15429== at 0x4024106: memalign (vg_replace_malloc.c:581) 158: ==15429== by 0x4024163: posix_memalign (vg_replace_malloc.c:709) 159: ==15429== by 0x40969C1: ??? (in /lib/libglib-2.0.so.0.2400.1) 160: ==15429== by 0x4097222: g_slice_alloc (in /lib/libglib-2.0.so.0.2400.1) 161: ==15429== by 0x40988A5: g_slist_append (in /lib/libglib-2.0.so.0.2400.1) 162: ==15429== by 0x80489D2: xyn_pl_get_files (xyn-playlist.c:58) 163: ==15429== by 0x8048848: main (main.c:18) 164: ==15429== 165: ==15429== 56,640 bytes in 472 blocks are possibly lost in loss record 10 of 11 166: ==15429== at 0x4024106: memalign (vg_replace_malloc.c:581) 167: ==15429== by 0x4024163: posix_memalign (vg_replace_malloc.c:709) 168: ==15429== by 0x40969C1: ??? (in /lib/libglib-2.0.so.0.2400.1) 169: ==15429== by 0x4097222: g_slice_alloc (in /lib/libglib-2.0.so.0.2400.1) 170: ==15429== by 0x40988A5: g_slist_append (in /lib/libglib-2.0.so.0.2400.1) 171: ==15429== by 0x8048A0D: xyn_pl_get_files (xyn-playlist.c:61) 172: ==15429== by 0x8048848: main (main.c:18) 173: ==15429== 174: ==15429== 685,118 bytes in 6,736 blocks are definitely lost in loss record 11 of 11 175: ==15429== at 0x4024F20: malloc (vg_replace_malloc.c:236) 176: ==15429== by 0x4081243: g_malloc (in /lib/libglib-2.0.so.0.2400.1) 177: ==15429== by 0x409B85B: g_strconcat (in /lib/libglib-2.0.so.0.2400.1) 178: ==15429== by 0x80489FE: xyn_pl_get_files (xyn-playlist.c:62) 179: ==15429== by 0x8048848: main (main.c:18) 180: ==15429== 181: ==15429== LEAK SUMMARY: 182: ==15429== definitely lost: 685,118 bytes in 6,736 blocks 183: ==15429== indirectly lost: 0 bytes in 0 blocks 184: ==15429== possibly lost: 62,769 bytes in 523 blocks 185: ==15429== still reachable: 3,564 bytes in 4 blocks 186: ==15429== suppressed: 0 bytes in 0 blocks 187: ==15429== 188: ==15429== For counts of detected and suppressed errors, rerun with: -v 189: ==15429== ERROR SUMMARY: 7 errors from 7 contexts (suppressed: 17 from 8) 190: ---------------------------------------------------------------------------------------------- I am using the above code in order to create a list with all the filepaths in a certain directory. (In my case fts.h or ftw.h are not an option). I am using GLib as the data structures library. Still I have my doubts in regarding the way GLib is allocating, de-allocating memory ? When invoking g_slist_free(list) i also free the data contained by the elements ? Why all those memory leaks appear ? Is valgrind a suitable tool for profilinf memory issues when using a complex library like GLib ? LATER EDIT: If I g_slist_foreach(l,(GFunc)g_free,NULL);, the valgrind report is different, (All the memory leaks from 'definitely lost' will move to 'indirectly lost'). Still I don't see the point ? Aren't GLib collections implement a way to be freed ?

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  • Sorting Algorithms

    - by MarkPearl
    General Every time I go back to university I find myself wading through sorting algorithms and their implementation in C++. Up to now I haven’t really appreciated their true value. However as I discovered this last week with Dictionaries in C# – having a knowledge of some basic programming principles can greatly improve the performance of a system and make one think twice about how to tackle a problem. I’m going to cover briefly in this post the following: Selection Sort Insertion Sort Shellsort Quicksort Mergesort Heapsort (not complete) Selection Sort Array based selection sort is a simple approach to sorting an unsorted array. Simply put, it repeats two basic steps to achieve a sorted collection. It starts with a collection of data and repeatedly parses it, each time sorting out one element and reducing the size of the next iteration of parsed data by one. So the first iteration would go something like this… Go through the entire array of data and find the lowest value Place the value at the front of the array The second iteration would go something like this… Go through the array from position two (position one has already been sorted with the smallest value) and find the next lowest value in the array. Place the value at the second position in the array This process would be completed until the entire array had been sorted. A positive about selection sort is that it does not make many item movements. In fact, in a worst case scenario every items is only moved once. Selection sort is however a comparison intensive sort. If you had 10 items in a collection, just to parse the collection you would have 10+9+8+7+6+5+4+3+2=54 comparisons to sort regardless of how sorted the collection was to start with. If you think about it, if you applied selection sort to a collection already sorted, you would still perform relatively the same number of iterations as if it was not sorted at all. Many of the following algorithms try and reduce the number of comparisons if the list is already sorted – leaving one with a best case and worst case scenario for comparisons. Likewise different approaches have different levels of item movement. Depending on what is more expensive, one may give priority to one approach compared to another based on what is more expensive, a comparison or a item move. Insertion Sort Insertion sort tries to reduce the number of key comparisons it performs compared to selection sort by not “doing anything” if things are sorted. Assume you had an collection of numbers in the following order… 10 18 25 30 23 17 45 35 There are 8 elements in the list. If we were to start at the front of the list – 10 18 25 & 30 are already sorted. Element 5 (23) however is smaller than element 4 (30) and so needs to be repositioned. We do this by copying the value at element 5 to a temporary holder, and then begin shifting the elements before it up one. So… Element 5 would be copied to a temporary holder 10 18 25 30 23 17 45 35 – T 23 Element 4 would shift to Element 5 10 18 25 30 30 17 45 35 – T 23 Element 3 would shift to Element 4 10 18 25 25 30 17 45 35 – T 23 Element 2 (18) is smaller than the temporary holder so we put the temporary holder value into Element 3. 10 18 23 25 30 17 45 35 – T 23   We now have a sorted list up to element 6. And so we would repeat the same process by moving element 6 to a temporary value and then shifting everything up by one from element 2 to element 5. As you can see, one major setback for this technique is the shifting values up one – this is because up to now we have been considering the collection to be an array. If however the collection was a linked list, we would not need to shift values up, but merely remove the link from the unsorted value and “reinsert” it in a sorted position. Which would reduce the number of transactions performed on the collection. So.. Insertion sort seems to perform better than selection sort – however an implementation is slightly more complicated. This is typical with most sorting algorithms – generally, greater performance leads to greater complexity. Also, insertion sort performs better if a collection of data is already sorted. If for instance you were handed a sorted collection of size n, then only n number of comparisons would need to be performed to verify that it is sorted. It’s important to note that insertion sort (array based) performs a number item moves – every time an item is “out of place” several items before it get shifted up. Shellsort – Diminishing Increment Sort So up to now we have covered Selection Sort & Insertion Sort. Selection Sort makes many comparisons and insertion sort (with an array) has the potential of making many item movements. Shellsort is an approach that takes the normal insertion sort and tries to reduce the number of item movements. In Shellsort, elements in a collection are viewed as sub-collections of a particular size. Each sub-collection is sorted so that the elements that are far apart move closer to their final position. Suppose we had a collection of 15 elements… 10 20 15 45 36 48 7 60 18 50 2 19 43 30 55 First we may view the collection as 7 sub-collections and sort each sublist, lets say at intervals of 7 10 60 55 – 20 18 – 15 50 – 45 2 – 36 19 – 48 43 – 7 30 10 55 60 – 18 20 – 15 50 – 2 45 – 19 36 – 43 48 – 7 30 (Sorted) We then sort each sublist at a smaller inter – lets say 4 10 55 60 18 – 20 15 50 2 – 45 19 36 43 – 48 7 30 10 18 55 60 – 2 15 20 50 – 19 36 43 45 – 7 30 48 (Sorted) We then sort elements at a distance of 1 (i.e. we apply a normal insertion sort) 10 18 55 60 2 15 20 50 19 36 43 45 7 30 48 2 7 10 15 18 19 20 30 36 43 45 48 50 55 (Sorted) The important thing with shellsort is deciding on the increment sequence of each sub-collection. From what I can tell, there isn’t any definitive method and depending on the order of your elements, different increment sequences may perform better than others. There are however certain increment sequences that you may want to avoid. An even based increment sequence (e.g. 2 4 8 16 32 …) should typically be avoided because it does not allow for even elements to be compared with odd elements until the final sort phase – which in a way would negate many of the benefits of using sub-collections. The performance on the number of comparisons and item movements of Shellsort is hard to determine, however it is considered to be considerably better than the normal insertion sort. Quicksort Quicksort uses a divide and conquer approach to sort a collection of items. The collection is divided into two sub-collections – and the two sub-collections are sorted and combined into one list in such a way that the combined list is sorted. The algorithm is in general pseudo code below… Divide the collection into two sub-collections Quicksort the lower sub-collection Quicksort the upper sub-collection Combine the lower & upper sub-collection together As hinted at above, quicksort uses recursion in its implementation. The real trick with quicksort is to get the lower and upper sub-collections to be of equal size. The size of a sub-collection is determined by what value the pivot is. Once a pivot is determined, one would partition to sub-collections and then repeat the process on each sub collection until you reach the base case. With quicksort, the work is done when dividing the sub-collections into lower & upper collections. The actual combining of the lower & upper sub-collections at the end is relatively simple since every element in the lower sub-collection is smaller than the smallest element in the upper sub-collection. Mergesort With quicksort, the average-case complexity was O(nlog2n) however the worst case complexity was still O(N*N). Mergesort improves on quicksort by always having a complexity of O(nlog2n) regardless of the best or worst case. So how does it do this? Mergesort makes use of the divide and conquer approach to partition a collection into two sub-collections. It then sorts each sub-collection and combines the sorted sub-collections into one sorted collection. The general algorithm for mergesort is as follows… Divide the collection into two sub-collections Mergesort the first sub-collection Mergesort the second sub-collection Merge the first sub-collection and the second sub-collection As you can see.. it still pretty much looks like quicksort – so lets see where it differs… Firstly, mergesort differs from quicksort in how it partitions the sub-collections. Instead of having a pivot – merge sort partitions each sub-collection based on size so that the first and second sub-collection of relatively the same size. This dividing keeps getting repeated until the sub-collections are the size of a single element. If a sub-collection is one element in size – it is now sorted! So the trick is how do we put all these sub-collections together so that they maintain their sorted order. Sorted sub-collections are merged into a sorted collection by comparing the elements of the sub-collection and then adjusting the sorted collection. Lets have a look at a few examples… Assume 2 sub-collections with 1 element each 10 & 20 Compare the first element of the first sub-collection with the first element of the second sub-collection. Take the smallest of the two and place it as the first element in the sorted collection. In this scenario 10 is smaller than 20 so 10 is taken from sub-collection 1 leaving that sub-collection empty, which means by default the next smallest element is in sub-collection 2 (20). So the sorted collection would be 10 20 Lets assume 2 sub-collections with 2 elements each 10 20 & 15 19 So… again we would Compare 10 with 15 – 10 is the winner so we add it to our sorted collection (10) leaving us with 20 & 15 19 Compare 20 with 15 – 15 is the winner so we add it to our sorted collection (10 15) leaving us with 20 & 19 Compare 20 with 19 – 19 is the winner so we add it to our sorted collection (10 15 19) leaving us with 20 & _ 20 is by default the winner so our sorted collection is 10 15 19 20. Make sense? Heapsort (still needs to be completed) So by now I am tired of sorting algorithms and trying to remember why they were so important. I think every year I go through this stuff I wonder to myself why are we made to learn about selection sort and insertion sort if they are so bad – why didn’t we just skip to Mergesort & Quicksort. I guess the only explanation I have for this is that sometimes you learn things so that you can implement them in future – and other times you learn things so that you know it isn’t the best way of implementing things and that you don’t need to implement it in future. Anyhow… luckily this is going to be the last one of my sorts for today. The first step in heapsort is to convert a collection of data into a heap. After the data is converted into a heap, sorting begins… So what is the definition of a heap? If we have to convert a collection of data into a heap, how do we know when it is a heap and when it is not? The definition of a heap is as follows: A heap is a list in which each element contains a key, such that the key in the element at position k in the list is at least as large as the key in the element at position 2k +1 (if it exists) and 2k + 2 (if it exists). Does that make sense? At first glance I’m thinking what the heck??? But then after re-reading my notes I see that we are doing something different – up to now we have really looked at data as an array or sequential collection of data that we need to sort – a heap represents data in a slightly different way – although the data is stored in a sequential collection, for a sequential collection of data to be in a valid heap – it is “semi sorted”. Let me try and explain a bit further with an example… Example 1 of Potential Heap Data Assume we had a collection of numbers as follows 1[1] 2[2] 3[3] 4[4] 5[5] 6[6] For this to be a valid heap element with value of 1 at position [1] needs to be greater or equal to the element at position [3] (2k +1) and position [4] (2k +2). So in the above example, the collection of numbers is not in a valid heap. Example 2 of Potential Heap Data Lets look at another collection of numbers as follows 6[1] 5[2] 4[3] 3[4] 2[5] 1[6] Is this a valid heap? Well… element with the value 6 at position 1 must be greater or equal to the element at position [3] and position [4]. Is 6 > 4 and 6 > 3? Yes it is. Lets look at element 5 as position 2. It must be greater than the values at [4] & [5]. Is 5 > 3 and 5 > 2? Yes it is. If you continued to examine this second collection of data you would find that it is in a valid heap based on the definition of a heap.

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  • Don&rsquo;t Forget! In-Memory Databases are Hot

    - by andrewbrust
    If you’re left scratching your head over SAP’s intention to acquire Sybase for almost $6 million, you’re not alone.  Despite Sybase’s 1990s reign as the supreme database standard in certain sectors (including Wall Street), the company’s flagship product has certainly fallen from grace.  Why would SAP pay a greater than 50% premium over Sybase’s closing price on the day of the announcement just to acquire a relational database which is firmly stuck in maintenance mode? Well there’s more to Sybase than the relational database product.  Take, for example, its mobile application platform.  It hit Gartner’s “Leaders’ Quadrant” in January of last year, and SAP needs a good mobile play.  Beyond the platform itself, Sybase has a slew of mobile services; click this link to look them over. There’s a second major asset that Sybase has though, and I wonder if it figured prominently into SAP’s bid: Sybase IQ.  Sybase IQ is a columnar database.  Columnar databases place values from a given database column contiguously, unlike conventional relational databases, which store all of a row’s data in close proximity.  Storing column values together works well in aggregation reporting scenarios, because the figures to be aggregated can be scanned in one efficient step.  It also makes for high rates of compression because values from a single column tend to be close to each other in magnitude and may contain long sequences of repeating values.  Highly compressible databases use much less disk storage and can be largely or wholly loaded into memory, resulting in lighting fast query performance.  For an ERP company like SAP, with its own legacy BI platform (SAP BW) and the entire range of Business Objects and Crystal Reports BI products (which it acquired in 2007) query performance is extremely important. And it’s a competitive necessity too.  QlikTech has built an entire company on a columnar, in-memory BI product (QlikView).  So too has startup company Vertica.  IBM’s TM1 product has been doing in-memory OLAP for years.  And guess who else has the in-memory religion?  Microsoft does, in the form of its new PowerPivot product.  I expect the technology in PowerPivot to become strategic to the full-blown SQL Server Analysis Services product and the entire Microsoft BI stack.  I sure don’t blame SAP for jumping on the in-memory bandwagon, if indeed the Sybase acquisition is, at least in part, motivated by that. It will be interesting to watch and see what SAP does with Sybase’s product line-up (assuming the acquisition closes), including the core database, the mobile platform, IQ, and even tools like PowerBuilder.  It is also fascinating to watch columnar’s encroachment on relational.  Perhaps this acquisition will be columnar’s tipping point and people will no longer see it as a fad.  Are you listening Larry Ellison?

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  • Macbook (non-pro, late 2010) Power Management Issues relating to Nvidia-Current drivers

    - by gbvitaobscura
    I have tried many potential solutions but to no avail! (this is going to be a long post) Essentially, when I first install ubuntu (I have tested 10.11-12.04 beta) I can change the brightness of the macbook backlight. One of the first things I usually do once my machine finishes installing is enter "sudo apt-get install nvidia-current" into the terminal to get my Nvidia graphics card set up. Before I install nvidia-current power management works flawlessly. After installing nvidia-current my graphics driver works mostly properly (more on that later). When I press F1 or F2 notify osd pops up and shows icon for the backlight along with a meter which changes according to how much I press F1 or F2, but the backlight does not change brightness at all. Two supplementary facts: when I am running off of battery power the backlight does not dim ever, also changing the backlight brightness through the terminal does not work (it recognizes the command but changes nothing). Things which did not work: 1. editing xorg.conf 2. python script/hack 3. editing grub Things which did work: 1. removing Nvidia-Current Final piece of information: Although my graphics card works in every way but Power Management it can not be found through System Settings/Details (Graphics Unknown) I'm using the NVIDIA GeForce 320M. the output of lspci is: 00:00.0 Host bridge: NVIDIA Corporation MCP89 HOST Bridge (rev a1) 00:00.1 RAM memory: NVIDIA Corporation MCP89 Memory Controller (rev a1) 00:01.0 RAM memory: NVIDIA Corporation Device 0d6d (rev a1) 00:01.1 RAM memory: NVIDIA Corporation Device 0d6e (rev a1) 00:01.2 RAM memory: NVIDIA Corporation Device 0d6f (rev a1) 00:01.3 RAM memory: NVIDIA Corporation Device 0d70 (rev a1) 00:02.0 RAM memory: NVIDIA Corporation Device 0d71 (rev a1) 00:02.1 RAM memory: NVIDIA Corporation Device 0d72 (rev a1) 00:03.0 ISA bridge: NVIDIA Corporation MCP89 LPC Bridge (rev a2) 00:03.1 RAM memory: NVIDIA Corporation MCP89 Memory Controller (rev a1) 00:03.2 SMBus: NVIDIA Corporation MCP89 SMBus (rev a1) 00:03.3 RAM memory: NVIDIA Corporation MCP89 Memory Controller (rev a1) 00:03.4 Co-processor: NVIDIA Corporation MCP89 Co-Processor (rev a1) 00:04.0 USB controller: NVIDIA Corporation MCP89 OHCI USB 1.1 Controller (rev a1) 00:04.1 USB controller: NVIDIA Corporation MCP89 EHCI USB 2.0 Controller (rev a2) 00:06.0 USB controller: NVIDIA Corporation MCP89 OHCI USB 1.1 Controller (rev a1) 00:06.1 USB controller: NVIDIA Corporation MCP89 EHCI USB 2.0 Controller (rev a2) 00:08.0 Audio device: NVIDIA Corporation MCP89 High Definition Audio (rev a2) 00:09.0 Ethernet controller: NVIDIA Corporation MCP89 Ethernet (rev a1) 00:0a.0 IDE interface: NVIDIA Corporation MCP89 SATA Controller (rev a2) 00:0b.0 RAM memory: NVIDIA Corporation Device 0d75 (rev a1) 00:15.0 PCI bridge: NVIDIA Corporation Device 0d9b (rev a1) 00:17.0 PCI bridge: NVIDIA Corporation MCP89 PCI Express Bridge (rev a1) 01:00.0 Network controller: Broadcom Corporation BCM43224 802.11a/b/g/n (rev 01) 02:00.0 VGA compatible controller: NVIDIA Corporation Device 08a0 (rev a2) There is a very similar bug on Launchpad which I have posted below. https://bugs.launchpad.net/ubuntu/+source/nvidia-graphics-drivers/+bug/764195

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  • CGBitmapContextCreate on the iPhone/iPad

    - by toastie
    Hello, I have a method that needs to parse through a bunch of large PNG images pixel by pixel (the PNGs are 600x600 pixels each). It seems to work great on the Simulator, but on the device (iPad), i get an EXC_BAD_ACCESS in some internal memory copying function. It seems the size is the culprit because if I try it on smaller images, everything seems to work. Here's the memory related meat of method below. + (CGRect) getAlphaBoundsForUImage: (UIImage*) image { CGImageRef imageRef = [image CGImage]; NSUInteger width = CGImageGetWidth(imageRef); NSUInteger height = CGImageGetHeight(imageRef); CGColorSpaceRef colorSpace = CGColorSpaceCreateDeviceRGB(); unsigned char *rawData = malloc(height * width * 4); memset(rawData,0,height * width * 4); NSUInteger bytesPerPixel = 4; NSUInteger bytesPerRow = bytesPerPixel * width; NSUInteger bitsPerComponent = 8; CGContextRef context = CGBitmapContextCreate(rawData, width, height, bitsPerComponent, bytesPerRow, colorSpace, kCGImageAlphaPremultipliedLast | kCGBitmapByteOrder32Big); CGColorSpaceRelease(colorSpace); CGContextDrawImage(context, CGRectMake(0, 0, width, height), imageRef); CGContextRelease(context); /* non-memory related stuff */ free(rawData); When I run this on a bunch of images, it runs 12 times and then craps out, while on the simulator it runs no problem. Do you guys have any ideas?

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  • How to dispose a Writeable Bitmap? (WPF)

    - by Mario
    Some time ago i posted a question related to a WriteableBitmap memory leak, and though I received wonderful tips related to the problem, I still think there is a serious bug / (mistake made by me) / (Confusion) / (some other thing) here. So, here is my problem again: Suppose we have a WPF application with an Image and a button. The image's source is a really big bitmap (3600 * 4800 px), when it's shown at runtime the applicaton consumes ~90 MB. Now suppose i wish to instantiate a WriteableBitmap from the source of the image (the really big Image), when this happens the applications consumes ~220 MB. Now comes the tricky part, when the modifications to the image (through the WriteableBitmap) end, and all the references to the WriteableBitmap (at least those that I'm aware of) are destroyed (at the end of a method or by setting them to null) the memory used by the writeableBitmap should be freed and the application consumption should return to ~90 MB. The problem is that sometimes it returns, sometimes it does not. Here is a sample code: // The Image's source whas set previous to this event private void buttonTest_Click(object sender, RoutedEventArgs e) { if (image.Source != null) { WriteableBitmap bitmap = new WriteableBitmap((BitmapSource)image.Source); bitmap.Lock(); bitmap.Unlock(); //image.Source = null; bitmap = null; } } As you can see the reference is local and the memory should be released at the end of the method (Or when the Garbage collector decides to do so). However, the app could consume ~224 MB until the end of the universe. Any help would be great.

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  • Clear UIWebView content upon dismissal of modal view (iPhone OS 3.0)

    - by Ricky
    I currently have a UIWebView that is displayed within a modal view. It is basically a detail view that provides a view of a page when the user clicks a link. When the view is dismissed and then brought up again (when the user clicks another link), the previously-loaded content is still visible and the new content loads "on top" of the last content. This makes sense because the instance of the UIWebView persists between sessions and is only released when the memory is needed. However, I would like to completely clear the UIWebView when the modal view is dismissed so that 1) content is cleared and 2) memory is freed. Thus far my research and attempts have not found an answer. These links haven't worked for me: http://stackoverflow.com/questions/2184688/is-it-possible-to-free-memory-of-uiwebview http://stackoverflow.com/questions/2311564/reused-uiwebview-showing-previous-loaded-content-for-a-brief-second-on-iphone I've tried [[NSURLCache sharedURLCache] removeAllCachedResponses]; and setting the webView to nil and manually releasing the webView upon modal-view-dismiss to no avail. Any thoughts from the wizened masses?

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  • Advice using leaks in instruments for noobs

    - by Gyozo Kudor
    Hello I am pretty new to iphone development. I have run my app for the first time using the "Leaks" from "Instruments". It shows me several leaks around 20 the smallest is 32 bytes and there is one with 1KB. I have followed the memory management guidelines, (i (think i) understand how and when to use release, not to use it when adding to autorelease pools, for every copy, retain, init there should be a release,... etc). I don't think I understand the output of the Leaks in instruments. What does "Responsible library" and "Responsible frame" mean. Because there are some classes and methods i never used directly. Are there any good tutorials for debugging memory leaks in instruments or other advice you can give me regarding leaks. Thanks in advance. Here are the largest 2 leaks. Leaked Object # Address Size Responsible Library Responsible Frame Malloc 1.00 KB 0x4827400 1024 CFNetwork std::vector *, std::allocator * ::reserve(unsigned long) // i have no idea what this is. Leaked Object # Address Size Responsible Library Responsible Frame Malloc 128 Bytes 5 640 UIKit UIImagePickerLoadPhotoLibraryIfNecessary // so this means UIImagePicker is leaking memory? The first leak i get Leaked Object # Address Size Responsible Library Responsible Frame Malloc 128 Bytes 0x442dfd0 128 UIKit UIKeyboardInputManagerClassForInputMode I don't understand any of those.

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  • Is there any danger in calling free() or delete instead of delete[]? [closed]

    - by Matt Joiner
    Possible Duplicate: ( POD )freeing memory : is delete[] equal to delete ? Does delete deallocate the elements beyond the first in an array? char *s = new char[n]; delete s; Does it matter in the above case seeing as all the elements of s are allocated contiguously, and it shouldn't be possible to delete only a portion of the array? For more complex types, would delete call the destructor of objects beyond the first one? Object *p = new Object[n]; delete p; How can delete[] deduce the number of Objects beyond the first, wouldn't this mean it must know the size of the allocated memory region? What if the memory region was allocated with some overhang for performance reasons? For example one could assume that not all allocators would provide a granularity of a single byte. Then any particular allocation could exceed the required size for each element by a whole element or more. For primitive types, such as char, int, is there any difference between: int *p = new int[n]; delete p; delete[] p; free p; Except for the routes taken by the respective calls through the delete-free deallocation machinery?

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  • Better why of looping to detect change.

    - by Dremation
    As of now I'm using a while(true) method to detect changes in memory. The problem with this is it's kill the applications performance. I have a list of 30 pointers that need checked as rapidly as possible for changes, without sacrificing a huge performance loss. Anyone have ideas on this? memScan = new Thread(ScanMem); public static void ScanMem() { int i = addy.Length; while (true) { Thread.Sleep(30000); //I do this to cut down on cpu usage for (int j = 0; j < i; j++) { string[] values = addy[j].Split(new char[] { Convert.ToChar(",") }); //MessageBox.Show(values[2]); try { if (Memory.Scanner.getIntFromMem(hwnd, (IntPtr)Convert.ToInt32(values[0], 16), 32).ToString() != values[1].ToString()) { //Ok, it changed lets do our work //work if (Globals.Working) return; SomeFunction("Results: " + values[2].ToString(), "Memory"); Globals.Working = true; }//end if }//end try catch { } }//end for }//end while }//end void

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  • understanding valgrind output

    - by sbsp
    Hi, i made a post earlier asking about checking for memory leaks etc, i did say i wasnt to familiar with the terminal in linux but someone said to me it was easy with valgrind i have managed to get it running etc but not to sure what the output means. Glancing over, all looks good to me but would like to run it past you experience folk for confirmation if possible. THe output is as follows ^C==2420== ==2420== HEAP SUMMARY: ==2420== in use at exit: 2,240 bytes in 81 blocks ==2420== total heap usage: 82 allocs, 1 frees, 2,592 bytes allocated ==2420== ==2420== LEAK SUMMARY: ==2420== definitely lost: 0 bytes in 0 blocks ==2420== indirectly lost: 0 bytes in 0 blocks ==2420== possibly lost: 0 bytes in 0 blocks ==2420== still reachable: 2,240 bytes in 81 blocks ==2420== suppressed: 0 bytes in 0 blocks ==2420== Reachable blocks (those to which a pointer was found) are not shown. ==2420== To see them, rerun with: --leak-check=full --show-reachable=yes ==2420== ==2420== For counts of detected and suppressed errors, rerun with: -v ==2420== ERROR SUMMARY: 0 errors from 0 contexts (suppressed: 13 from 8) Is all good here? the only thing concerning me is the still reachable part. Is that ok? Thanks everyone

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  • Can't get past 2542 Threads in Java on 4GB iMac OSX 10.6.3 Snow Leopard (32bit)

    - by fuzzy lollipop
    I am running the following program trying to figure out how to configure my JVM to get the maximum number of threads my machine can support. For those that might not know, Snow Leopard ships with Java 6. I tried starting it with defaults, and the following command lines, I always get the Out of Memory Error at Thread 2542 no matter what the JVM options are set to. java TestThreadStackSizes 100000 java -Xss1024 TestThreadStackSizes 100000 java -Xmx128m -Xss1024 TestThreadStackSizes 100000 java -Xmx2048m -Xss1024 TestThreadStackSizes 100000 java -Xmx2048m -Xms2048m -Xss1024 TestThreadStackSizes 100000 no matter what I pass it, I get the same results, Out of Memory Error at 2542 public class TestThreadStackSizes { public static void main(final String[] args) { Thread.currentThread().setUncaughtExceptionHandler(new Thread.UncaughtExceptionHandler() { public void uncaughtException(final Thread t, final Throwable e) { System.err.println(e.getMessage()); System.exit(1); } }); int numThreads = 1000; if (args.length == 1) { numThreads = Integer.parseInt(args[0]); } for (int i = 0; i < numThreads; i++) { try { Thread t = new Thread(new SleeperThread(i)); t.start(); } catch (final OutOfMemoryError e) { throw new RuntimeException(String.format("Out of Memory Error on Thread %d", i), e); } } } private static class SleeperThread implements Runnable { private final int i; private SleeperThread(final int i) { this.i = i; } public void run() { try { System.out.format("Thread %d about to sleep\n", this.i); Thread.sleep(1000 * 60 * 60); } catch (final InterruptedException e) { throw new RuntimeException(e); } } } } Any ideas on now I can affect these results?

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  • Java OutOfMemoryError message changes when trying to create Arrays of different sizes

    - by Gordon
    In the question by DKSRathore How to simulate the Out Of memory : Requested array size exceeds VM limit some odd behavior was noted when creating an arrays. When creating an array of size Integer.MAX_VALUE an exception with the error java.lang.OutOfMemoryError Requested array size exceeds VM limit was thrown. However when an array was created with a size less than the max but still above the virtual machine memory limit the error message read java.lang.OutOfMemoryError: Java heap space. Testing further I managed to narrow down where the error messages changes. long[] l = new long[2147483645]; exceptions message reads - Requested array size exceeds VM limit long[] l = new long[2147483644]; exceptions message reads - Java heap space errors I increased my virtual machine memory and still produced the same result. Has anyone any idea why this happens? Some extra info: Integer.MAX_VALUE = 2147483647. Edit: Here's the code I used to find the value, might be helpful. int max = Integer.MAX_VALUE; boolean done = false; while (!done) { try { max--; // Throws an error long[] l = new long[max]; // Exit if an error is no longer thrown done = true; } catch (OutOfMemoryError e) { if (!e.getMessage().contains("Requested array size exceeds VM limit")) { System.out.println("Message changes at " + max); done = true; } } }

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  • Better way of looping to detect change.

    - by Dremation
    As of now I'm using a while(true) method to detect changes in memory. The problem with this is it's kill the applications performance. I have a list of 30 pointers that need checked as rapidly as possible for changes, without sacrificing a huge performance loss. Anyone have ideas on this? memScan = new Thread(ScanMem); public static void ScanMem() { int i = addy.Length; while (true) { Thread.Sleep(30000); //I do this to cut down on cpu usage for (int j = 0; j < i; j++) { string[] values = addy[j].Split(new char[] { Convert.ToChar(",") }); //MessageBox.Show(values[2]); try { if (Memory.Scanner.getIntFromMem(hwnd, (IntPtr)Convert.ToInt32(values[0], 16), 32).ToString() != values[1].ToString()) { //Ok, it changed lets do our work //work if (Globals.Working) return; SomeFunction("Results: " + values[2].ToString(), "Memory"); Globals.Working = true; }//end if }//end try catch { } }//end for }//end while }//end void

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  • Preventing a heavy process from sinking in the swap file

    - by eran
    Our service tends to fall asleep during the nights on our client's server, and then have a hard time waking up. What seems to happen is that the process heap, which is sometimes several hundreds of MB, is moved to the swap file. This happens at night, when our service is not used, and others are scheduled to run (DB backups, AV scans etc). When this happens, after a few hours of inactivity the first call to the service takes up to a few minutes (consequent calls take seconds). I'm quite certain it's an issue of virtual memory management, and I really hate the idea of forcing the OS to keep our service in the physical memory. I know doing that will hurt other processes on the server, and decrease the overall server throughput. Having that said, our clients just want our app to be responsive. They don't care if nightly jobs take longer. I vaguely remember there's a way to force Windows to keep pages on the physical memory, but I really hate that idea. I'm leaning more towards some internal or external watchdog that will initiate higher-level functionalities (there is already some internal scheduler that does very little, and makes no difference). If there were a 3rd party tool that provided that kind of service is would have been just as good. I'd love to hear any comments, recommendations and common solutions to this kind of problem. The service is written in VC2005 and runs on Windows servers.

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  • release object of a return method object c

    - by Piero
    in run the app with the analyze build, and Xcode found me a lot of memory leak and there is one in particular that i don't know how solve here it is: - (UIView *) tableView:(UITableView *)tableView viewForHeaderInSection:(NSInteger)section { UIImageView *sectionImage = [[UIImageView alloc] init]; if (section == 0)sectionImage.image = [UIImage imageNamed:@"myImage.png"]; return sectionImage; } so my question is, how i can release this sectionImage? if is the return of the method? EDIT: i have another question, analyze give me another memory leak, i have this: .h @property (nonatomic, retain) NSIndexPath *directCellPath; .m @synthesize directCellPath = _directCellPath; - (id)init{ if ((self = [super initWithNibName:@"MyViewController" bundle:nil])) { self.directCellPath = [[NSIndexPath alloc] init]; } return self; } then in the code i use it and finally in the dealloc i do this: - (void)dealloc { [_directCellPath release]; [super dealloc]; } and give me a memory leak on this line: self.directCellPath = [[NSIndexPath alloc] init]; why if i have deallocated it in the dealloc?

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  • Large ListView containing images in Android

    - by Marco W.
    For various Android applications, I need large ListViews, i.e. such views with 100-300 entries. All entries must be loaded in bulk when the application is started, as some sorting and processing is necessary and the application cannot know which items to display first, otherwise. So far, I've been loading the images for all items in bulk as well, which are then saved in an ArrayList<CustomType> together with the rest of the data for each entry. But of course, this is not a good practice, as you're very likely to have an OutOfMemoryException then: The references to all images in the ArrayList prevent the garbage collector from working. So the best solution is, obviously, to load only the text data in bulk whereas the images are then loaded as needed, right? The Google Play application does this, for example: You can see that images are loaded as you scroll to them, i.e. they are probably loaded in the adapter's getView() method. But with Google Play, this is a different problem, anyway, as the images must be loaded from the Internet, which is not the case for me. My problem is not that loading the images takes too long, but storing them requires too much memory. So what should I do with the images? Load in getView(), when they are really needed? Would make scrolling sluggish. So calling an AsyncTask then? Or just a normal Thread? Parametrize it? I could save the images that are already loaded into a HashMap<String,Bitmap>, so that they don't need to be loaded again in getView(). But if this is done, you have the memory problem again: The HashMap stores references to all images, so in the end, you could have the OutOfMemoryException again. I know that there are already lots of questions here that discuss "Lazy loading" of images. But they mainly cover the problem of slow loading, not too much memory consumption.

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  • Memory leak with objective-c on alloc

    - by Grunzig
    When I use Instruments to find memory leaks, a leak is detected on Horaires *jour; jour= [[Horaires alloc] init]; // memory leak reported here by Instruments self.lundi = jour; [jour release]; and I don't know why there is a leak at this point. Does anyone can help me? Here's the code. // HorairesCollection.h #import <Foundation/Foundation.h> #import "Horaires.h" @interface HorairesCollection : NSObject < NSCopying > { Horaires *lundi; } @property (nonatomic, retain) Horaires *lundi; -init; -(void)dealloc; @end // HorairesCollection.m #import "HorairesCollection.h" @implementation HorairesCollection @synthesize lundi; -(id)copyWithZone:(NSZone *)zone{ DefibHoraires *another = [[DefibHoraires alloc] init]; another.lundi = [lundi copyWithZone: zone]; [another autorelease]; return another; } -init{ self = [super init]; Horaires *jour; jour= [[Horaires alloc] init]; // memory leak reported here by Instruments self.lundi = jour; [jour release]; return self; } - (void)dealloc { [lundi release]; [super dealloc]; } @end // Horaires.h #import <Foundation/Foundation.h> @interface Horaires : NSObject <NSCopying>{ BOOL ferme; BOOL h24; NSString *h1; } @property (nonatomic, assign) BOOL ferme; @property (nonatomic, assign) BOOL h24; @property (nonatomic, retain) NSString *h1; -init; -(id)copyWithZone:(NSZone *)zone; -(void)dealloc; @end // Horaires.m #import "Horaires.h" @implementation Horaires -(BOOL) ferme { return ferme; } -(void)setFerme:(BOOL)bFerme{ ferme = bFerme; if (ferme) { self.h1 = @""; self.h24 = NO; } } -(BOOL) h24 { return h24; } -(void)setH24:(BOOL)bH24{ h24 = bH24; if (h24) { self.h1 = @""; self.ferme = NO; } } -(NSString *) h1 { return h1; } -(void)setH1:(NSString *)horaire{ [horaire retain]; [h1 release]; h1 = horaire; if (![h1 isEqualToString:@""]) { self.h24 = NO; self.ferme = NO; } } -(id)copyWithZone:(NSZone *)zone{ Horaires *another = [[Horaires alloc] init]; another.ferme = self.ferme; another.h24 = self.h24; another.h1 = self.h1; [another autorelease]; return another; } -init{ self = [super init]; return self; } -(void)dealloc { [h1 release]; [super dealloc]; } @end

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