Search Results

Search found 15401 results on 617 pages for 'memory optimization'.

Page 98/617 | < Previous Page | 94 95 96 97 98 99 100 101 102 103 104 105  | Next Page >

  • Search Engine Optimization For Beginners

    Learning about the SEO techniques can be scary and a bit overwhelming to say the least. If you do not know anything about SEO now is the time to learn, before trying to do it with just a little bit of knowledge, you will fail if you do it that way.

    Read the article

  • Search Engine Optimization

    The best way a company can inform its public about itself is through its website. Most corporations and firms today have a website to their name. The internet has proved itself to be an open market for all kinds of products; the only problem being the trouble of attracting internet users.

    Read the article

  • 7 Steps to Search Engine Optimization

    Internet Marketing is a new media and latest trend to advertising which moving away from conventional advertising like print media, electronic media and etc. Internet marketing is a holistic and effective approach on internet to reach wider and more defined target marketing.

    Read the article

  • Search Engine Optimization Terms

    By the time you complete this multiple lesson tutorial, you'll know just what it takes to score top search engine positions for your Web sites. You'll understand how search engines crawl the Web, how they rank Web sites, and how they find previously undiscovered sites. You'll master the important HTML tags that are your key to getting your sites on a search engine's radar, and you'll see why it's important to amass as many potential keywords as possible.

    Read the article

  • What is SEO (Search Engine Optimization)?

    SEO in its most basic form is a series of steps taken to make a web site search engine friendly and have it show up in the search engines. At a more advanced level, SEO can be implemented to allow the web site in question to rank high in the search engines, preferably in the first few positions.

    Read the article

  • Nginx , Apache , Mysql , Memcache with server 4G ram. How optimize to enoigh of memory?

    - by TomSawyer
    i have 1 dedicated server with Nginx proxy for Apache. Memcache, mysql, 4G Ram. These day, my visitor on my site wasn't increased, but my server get overload always in some specified time. (9AM - 15PM) Ram in use is increased second by second to full. that's moment, my server will get overload. i have to kill all apache , mysql service and reboot it to get free memory. and it'll full again. that's the terrible circle. here is my ram in use at the moment 160(nginx) 220(apache) 512(memcache) 924(mysql) here's process number 4(nginx) 14(apache) 5(memcache) 20(mysql) and here's my my.cnf config. someone can help me to optimize it? [mysqld] datadir=/var/lib/mysql socket=/var/lib/mysql/mysql.sock user=mysql skip-locking skip-networking skip-name-resolve # enable log-slow-queries log-slow-queries = /var/log/mysql-slow-queries.log long_query_time=3 max_connections=200 wait_timeout=64 connect_timeout = 10 interactive_timeout = 25 thread_stack = 512K max_allowed_packet=16M table_cache=1500 read_buffer_size=4M join_buffer_size=4M sort_buffer_size=4M read_rnd_buffer_size = 4M max_heap_table_size=256M tmp_table_size=256M thread_cache=256 query_cache_type=1 query_cache_limit=4M query_cache_size=16M thread_concurrency=8 myisam_sort_buffer_size=128M # Disabling symbolic-links is recommended to prevent assorted security risks symbolic-links=0 [mysqldump] quick max_allowed_packet=16M [mysql] no-auto-rehash [isamchk] key_buffer=256M sort_buffer=256M read_buffer=64M write_buffer=64M [myisamchk] key_buffer=256M sort_buffer=256M read_buffer=64M write_buffer=64M [mysqlhotcopy] interactive-timeout [mysql.server] user=mysql basedir=/var/lib [mysqld_safe] log-error=/var/log/mysqld.log pid-file=/var/run/mysqld/mysqld.pid

    Read the article

  • Inline function v. Macro in C -- What's the Overhead (Memory/Speed)?

    - by Jason R. Mick
    I searched Stack Overflow for the pros/cons of function-like macros v. inline functions. I found the following discussion: Pros and Cons of Different macro function / inline methods in C ...but it didn't answer my primary burning question. Namely, what is the overhead in c of using a macro function (with variables, possibly other function calls) v. an inline function, in terms of memory usage and execution speed? Are there any compiler-dependent differences in overhead? I have both icc and gcc at my disposal. My code snippet I'm modularizing is: double AttractiveTerm = pow(SigmaSquared/RadialDistanceSquared,3); double RepulsiveTerm = AttractiveTerm * AttractiveTerm; EnergyContribution += 4 * Epsilon * (RepulsiveTerm - AttractiveTerm); My reason for turning it into an inline function/macro is so I can drop it into a c file and then conditionally compile other similar, but slightly different functions/macros. e.g.: double AttractiveTerm = pow(SigmaSquared/RadialDistanceSquared,3); double RepulsiveTerm = pow(SigmaSquared/RadialDistanceSquared,9); EnergyContribution += 4 * Epsilon * (RepulsiveTerm - AttractiveTerm); (note the difference in the second line...) This function is a central one to my code and gets called thousands of times per step in my program and my program performs millions of steps. Thus I want to have the LEAST overhead possible, hence why I'm wasting time worrying about the overhead of inlining v. transforming the code into a macro. Based on the prior discussion I already realize other pros/cons (type independence and resulting errors from that) of macros... but what I want to know most, and don't currently know is the PERFORMANCE. I know some of you C veterans will have some great insight for me!!

    Read the article

  • linux new/delete, malloc/free large memory blocks

    - by brian_mk
    Hi folks, We have a linux system (kubuntu 7.10) that runs a number of CORBA Server processes. The server software uses glibc libraries for memory allocation. The linux PC has 4G physical memory. Swap is disabled for speed reasons. Upon receiving a request to process data, one of the server processes allocates a large data buffer (using the standard C++ operator 'new'). The buffer size varies depening upon a number of parameters but is typically around 1.2G Bytes. It can be up to about 1.9G Bytes. When the request has completed, the buffer is released using 'delete'. This works fine for several consecutive requests that allocate buffers of the same size or if the request allocates a smaller size than the previous. The memory appears to be free'd ok - otherwise buffer allocation attempts would eventually fail after just a couple of requests. In any case, we can see the buffer memory being allocated and freed for each request using tools such as KSysGuard etc. The problem arises when a request requires a buffer larger than the previous. In this case, operator 'new' throws an exception. It's as if the memory that has been free'd from the first allocation cannot be re-allocated even though there is sufficient free physical memory available. If I kill and restart the server process after the first operation, then the second request for a larger buffer size succeeds. i.e. killing the process appears to fully release the freed memory back to the system. Can anyone offer an explanation as to what might be going on here? Could it be some kind of fragmentation or mapping table size issue? I am thinking of replacing new/delete with malloc/free and use mallopt to tune the way the memory is being released to the system. BTW - I'm not sure if it's relevant to our problem, but the server uses Pthreads that get created and destroyed on each processing request. Cheers, Brian.

    Read the article

  • JavaME - LWUIT images eat up all the memory

    - by Marko
    Hi, I'm writing a MIDlet using LWUIT and images seem to eat up incredible amounts of memory. All the images I use are PNGs and are packed inside the JAR file. I load them using the standard Image.createImage(URL) method. The application has a number of forms and each has a couple of labels an buttons, however I am fairly certain that only the active form is kept in memory (I know it isn't very trustworthy, but Runtime.freeMemory() seems to confirm this). The application has worked well in 240x320 resolution, but moving it to 480x640 and using appropriately larger images for UI started causing out of memory errors to show up. What the application does, among other things, is download remote images. The application seems to work fine until it gets to this point. After downloading a couple of PNGs and returning to the main menu, the out of memory error is encountered. Naturally, I looked into the amount of memory the main menu uses and it was pretty shocking. It's just two labels with images and four buttons. Each button has three images used for style.setIcon, setPressedIcon and setRolloverIcon. Images range in size from 15 to 25KB but removing two of the three images used for every button (so 8 images in total), Runtime.freeMemory() showed a stunning 1MB decrease in memory usage. The way I see it, I either have a whole lot of memory leaks (which I don't think I do, but memory leaks aren't exactly known to be easily tracked down), I am doing something terribly wrong with image handling or there's really no problem involved and I just need to scale down. If anyone has any insight to offer, I would greatly appreciate it.

    Read the article

  • Memory mapping of files and system cache behavior in WinXP

    - by Canopus
    Our application is memory intensive and deals with reading a large number of disk files. The total load can be more than 3 GB. There is a custom memory manager that uses memory mapped files to achieve reading of such a huge data. The files are mapped into the process memory space only when needed and with this the process memory is well under control. But what is observed is, with memory mapping, the system cache keeps on increasing until it occupies the available physical memory. This leads to the slowing down of the entire system. My question is how to prevent system cache from hogging the physical memory? I attempted to remove the file buffering (by using FILE_FLAG_NO_BUFFERING ), but with this, the read operations take considerable amount of time and slows down the application performance. How to achieve the scalability without sacrificing much on performance. What are the common techniques used in such cases? I dont have a good understanding of the WinXP OS caching behavior. Any good links explaining the same would also be helpful.

    Read the article

  • Why is WPO(whole-program optimization) not doing any improvements in my program size? (FPC 2.4.0)

    - by Gregory Smith
    I use FPC 2.4.0 for WinXP(binary from the official page), also tryed with same version but compiled from source on my comp. I put something like this: I:\pascal\fpc-2.4.0.source\fpc-2.4.0\compiler\ppc386 -FWserver-1.wpo -OWsymbolliveness -CX -XX -Xs- -al -Os -oServer1.o Server I:\pascal\fpc-2.4.0.source\fpc-2.4.0\compiler\ppc386 -FWserver-2.wpo -OWsymbolliveness -Fwserver-1.wpo -Owsymbolliveness -CX -XX -Xs- -al -Os -oServer2.o Server ..(up to 100 times) but always same .wpo files, and same .o sizes(.s, assembly files change intermittently) I also not(through compiler messages), that not used variables are still alive. Also tryed -OWall -owall What am i doing wrong?

    Read the article

  • Pure Java open-source libraries for portfolio selection (= constrained, non-linear optimization)?

    - by __roland__
    Does anyone know or has experience with a pure Java library to select portfolios or do some similar kinds of quadratic programming with constraints? There seems to be a lot of tools, as already discussed elsewhere - but what I would like to use is a pure Java implementation. Since I want to call the library from within another open-source software with a BSD-ish license I would prefer LGPL over GPL. Any help is appreciated. If you don't know such libraries, which is the most simple algorithm you would suggest to implement? It has to cope with an inequality constraint (all x_i = 0) and an equality constraint (sum of all x_i = 1).

    Read the article

  • Mysql optimization question - How to apply AND logic in search and limit on results in one query?

    - by sandeepan-nath
    This is a little long but I have provided all the database structures and queries so that you can run it immediately and help me. Run the following queries:- CREATE TABLE IF NOT EXISTS `Tutor_Details` ( `id_tutor` int(10) NOT NULL auto_increment, `firstname` varchar(100) NOT NULL default '', `surname` varchar(155) NOT NULL default '', PRIMARY KEY (`id_tutor`) ) ENGINE=InnoDB DEFAULT CHARSET=latin1 AUTO_INCREMENT=41 ; INSERT INTO `Tutor_Details` (`id_tutor`,`firstname`, `surname`) VALUES (1, 'Sandeepan', 'Nath'), (2, 'Bob', 'Cratchit'); CREATE TABLE IF NOT EXISTS `Classes` ( `id_class` int(10) unsigned NOT NULL auto_increment, `id_tutor` int(10) unsigned NOT NULL default '0', `class_name` varchar(255) default NULL, PRIMARY KEY (`id_class`) ) ENGINE=InnoDB DEFAULT CHARSET=utf8 AUTO_INCREMENT=229 ; INSERT INTO `Classes` (`id_class`,`class_name`, `id_tutor`) VALUES (1, 'My Class', 1), (2, 'Sandeepan Class', 2); CREATE TABLE IF NOT EXISTS `Tags` ( `id_tag` int(10) unsigned NOT NULL auto_increment, `tag` varchar(255) default NULL, PRIMARY KEY (`id_tag`), UNIQUE KEY `tag` (`tag`), KEY `id_tag` (`id_tag`), KEY `tag_2` (`tag`), KEY `tag_3` (`tag`) ) ENGINE=InnoDB DEFAULT CHARSET=latin1 AUTO_INCREMENT=18 ; INSERT INTO `Tags` (`id_tag`, `tag`) VALUES (1, 'Bob'), (6, 'Class'), (2, 'Cratchit'), (4, 'Nath'), (3, 'Sandeepan'), (5, 'My'); CREATE TABLE IF NOT EXISTS `Tutors_Tag_Relations` ( `id_tag` int(10) unsigned NOT NULL default '0', `id_tutor` int(10) default NULL, KEY `Tutors_Tag_Relations` (`id_tag`), KEY `id_tutor` (`id_tutor`), KEY `id_tag` (`id_tag`) ) ENGINE=InnoDB DEFAULT CHARSET=latin1; INSERT INTO `Tutors_Tag_Relations` (`id_tag`, `id_tutor`) VALUES (3, 1), (4, 1), (1, 2), (2, 2); CREATE TABLE IF NOT EXISTS `Class_Tag_Relations` ( `id_tag` int(10) unsigned NOT NULL default '0', `id_class` int(10) default NULL, `id_tutor` int(10) NOT NULL, KEY `Class_Tag_Relations` (`id_tag`), KEY `id_class` (`id_class`), KEY `id_tag` (`id_tag`) ) ENGINE=InnoDB DEFAULT CHARSET=latin1; INSERT INTO `Class_Tag_Relations` (`id_tag`, `id_class`, `id_tutor`) VALUES (5, 1, 1), (6, 1, 1), (3, 2, 2), (6, 2, 2); Following is about the tables:- There are tutors who create classes. Tutor_Details - Stores tutors Classes - Stores classes created by tutors And for searching we are using a tags based approach. All the keywords are stored in tags table (while classes/tutors are created) and tag relations are entered in Tutor_Tag_Relations and Class_Tag_Relations tables (for tutors and classes respectively)like this:- Tags - id_tag tag (this is a a unique field) Tutors_Tag_Relations - Stores tag relations while the tutors are created. Class_Tag_Relations - Stores tag relations while any tutor creates a class In the present data in database, tutor "Sandeepan Nath" has has created class "My Class" and "Bob Cratchit" has created "Sandeepan Class". 3.Requirement The requirement is to return tutor records from Tutor_Details table such that all the search terms (AND logic) are present in the union of these two sets - 1. Tutor_Details table 2. classes created by a tutor in Classes table) Example search and expected results:- Search Term Result "Sandeepan Class" Tutor Sandeepan Nath's record from Tutor Details table "Class" Both the tutors from ... Most importantly, there should be only one mysql query and a LIMIT applicable on the number of results. Following is a working query which I have so far written (It just applies OR logic of search key words instead of the desired AND logic). SELECT td . * FROM Tutor_Details AS td LEFT JOIN Tutors_Tag_Relations AS ttagrels ON td.id_tutor = ttagrels.id_tutor LEFT JOIN Classes AS wc ON td.id_tutor = wc.id_tutor INNER JOIN Class_Tag_Relations AS wtagrels ON td.id_tutor = wtagrels.id_tutor LEFT JOIN Tags AS t ON t.id_tag = ttagrels.id_tag OR t.id_tag = wtagrels.id_tag WHERE t.tag LIKE '%Sandeepan%' OR t.tag LIKE '%Nath%' GROUP BY td.id_tutor LIMIT 20 Please help me with anything you can. Thanks

    Read the article

  • Some optimization about the code (computing ranks of a vector)?

    - by user1748356
    The following code is a function (performance-critical) to compute tied ranks of a vector: mergeSort(x,inds,ci); //a sort function to sort vector x of length ci, also returns keys (inds) of x. int tj=0; double xi=x[0]; for (int j = 1; j < ci; ++j) { if (x[j] > xi) { double rankvalue = 0.5 * (j - 1 + tj); for (int k = tj; k < j; ++k) { ranks[inds[k]]=rankvalue; }; tj = j; xi = x[j]; }; }; double rankvalue = 0.5 * (ci - 1 + tj); for (int k = tj; k < ci; ++k) { ranks[inds[k]]=rankvalue; }; The problem is, the supposed performance bottleneck mergeSort(), which is O(NlogN) is several times faster than the other part of codes (which is O(N)), which suggests there is room for huge improvment with the other part of the codes, any advices?

    Read the article

< Previous Page | 94 95 96 97 98 99 100 101 102 103 104 105  | Next Page >