Search Results

Search found 8262 results on 331 pages for 'optimization algorithm'.

facebook twitter digg google delicious technorati stumbleupon myspace wordpress linkedin gmail igoogle windows live tumblr viadeo yahoo buzz yahoo mail yahoo bookmarks favorites email print

Page 148/331 | < Previous Page | 144 145 146 147 148 149 150 151 152 153 154 155  | Next Page >

  • Metamorphic generator

    - by user222094
    I am trying to find references about different designs of metamorphic generators can someone point me to the right direction. I have gone through some papers in ACM but couldn't find what I am looking for.

    Read the article

  • Python: Determine whether list of lists contains a defined sequence

    - by duhaime
    I have a list of sublists, and I want to see if any of the integer values from the first sublist plus one are contained in the second sublist. For all such values, I want to see if that value plus one is contained in the third sublist, and so on, proceeding in this fashion across all sublists. If there is a way of proceeding in this fashion from the first sublist to the last sublist, I wish to return True; otherwise I wish to return False. In other words, for each value in sublist one, for each "step" in a "walk" across all sublists read left to right, if that value + n (where n = number of steps taken) is contained in the current sublist, the function should return True; otherwise it should return False. (Sorry for the clumsy phrasing--I'm not sure how to clean up my language without using many more words.) Here's what I wrote. a = [ [1,3],[2,4],[3,5],[6],[7] ] def find_list_traversing_walk(l): for i in l[0]: index_position = 0 first_pass = 1 walking_current_path = 1 while walking_current_path == 1: if first_pass == 1: first_pass = 0 walking_value = i if walking_value+1 in l[index_position + 1]: index_position += 1 walking_value += 1 if index_position+1 == len(l): print "There is a walk across the sublists for initial value ", walking_value - index_position return True else: walking_current_path = 0 return False print find_list_traversing_walk(a) My question is: Have I overlooked something simple here, or will this function return True for all true positives and False for all true negatives? Are there easier ways to accomplish the intended task? I would be grateful for any feedback others can offer!

    Read the article

  • How to determine if two strings are sufficiently close?

    - by A.06
    We say that we can "hop" from the word w1 to the word w2 if they are "sufficiently close". We define w2 to be sufficiently close to w1 if one of the following holds: w2 is obtained from w1 by deleting one letter. w2 is obtained from w1 by replacing one of the letters in w1 by some letter that appears to its right in w1 and which is also to its right in alphabetical order. I have no idea how to check if 2. is fulfilled. To check if 1. is possible this is my function: bool check1(string w1, string w2){ if(w2.length - w1.length != 1){ return false; } for(int i = 0,int j = 0;i < w2.length;i++;j++){ if(w2[i] == w1[j]){//do nothing } else if(i == j){ j++; } else{ return false; } } return true; } Given two words w1 and w2, how do we check if we can 'hop' from w1 to w2?

    Read the article

  • Python performance improvement request for winkler

    - by Martlark
    I'm a python n00b and I'd like some suggestions on how to improve the algorithm to improve the performance of this method to compute the Jaro-Winkler distance of two names. def winklerCompareP(str1, str2): """Return approximate string comparator measure (between 0.0 and 1.0) USAGE: score = winkler(str1, str2) ARGUMENTS: str1 The first string str2 The second string DESCRIPTION: As described in 'An Application of the Fellegi-Sunter Model of Record Linkage to the 1990 U.S. Decennial Census' by William E. Winkler and Yves Thibaudeau. Based on the 'jaro' string comparator, but modifies it according to whether the first few characters are the same or not. """ # Quick check if the strings are the same - - - - - - - - - - - - - - - - - - # jaro_winkler_marker_char = chr(1) if (str1 == str2): return 1.0 len1 = len(str1) len2 = len(str2) halflen = max(len1,len2) / 2 - 1 ass1 = '' # Characters assigned in str1 ass2 = '' # Characters assigned in str2 #ass1 = '' #ass2 = '' workstr1 = str1 workstr2 = str2 common1 = 0 # Number of common characters common2 = 0 #print "'len1', str1[i], start, end, index, ass1, workstr2, common1" # Analyse the first string - - - - - - - - - - - - - - - - - - - - - - - - - # for i in range(len1): start = max(0,i-halflen) end = min(i+halflen+1,len2) index = workstr2.find(str1[i],start,end) #print 'len1', str1[i], start, end, index, ass1, workstr2, common1 if (index > -1): # Found common character common1 += 1 #ass1 += str1[i] ass1 = ass1 + str1[i] workstr2 = workstr2[:index]+jaro_winkler_marker_char+workstr2[index+1:] #print "str1 analyse result", ass1, common1 #print "str1 analyse result", ass1, common1 # Analyse the second string - - - - - - - - - - - - - - - - - - - - - - - - - # for i in range(len2): start = max(0,i-halflen) end = min(i+halflen+1,len1) index = workstr1.find(str2[i],start,end) #print 'len2', str2[i], start, end, index, ass1, workstr1, common2 if (index > -1): # Found common character common2 += 1 #ass2 += str2[i] ass2 = ass2 + str2[i] workstr1 = workstr1[:index]+jaro_winkler_marker_char+workstr1[index+1:] if (common1 != common2): print('Winkler: Wrong common values for strings "%s" and "%s"' % \ (str1, str2) + ', common1: %i, common2: %i' % (common1, common2) + \ ', common should be the same.') common1 = float(common1+common2) / 2.0 ##### This is just a fix ##### if (common1 == 0): return 0.0 # Compute number of transpositions - - - - - - - - - - - - - - - - - - - - - # transposition = 0 for i in range(len(ass1)): if (ass1[i] != ass2[i]): transposition += 1 transposition = transposition / 2.0 # Now compute how many characters are common at beginning - - - - - - - - - - # minlen = min(len1,len2) for same in range(minlen+1): if (str1[:same] != str2[:same]): break same -= 1 if (same > 4): same = 4 common1 = float(common1) w = 1./3.*(common1 / float(len1) + common1 / float(len2) + (common1-transposition) / common1) wn = w + same*0.1 * (1.0 - w) return wn

    Read the article

  • Wrappers of primitive types in arraylist vs arrays

    - by ismail marmoush
    Hi, In "Core java 1" I've read CAUTION: An ArrayList is far less efficient than an int[] array because each value is separately wrapped inside an object. You would only want to use this construct for small collections when programmer convenience is more important than efficiency. But in my software I've already used Arraylist instead of normal arrays due to some requirements, though "The software is supposed to have high performance and after I've read the quoted text I started to panic!" one thing I can change is changing double variables to Double so as to prevent auto boxing and I don't know if that is worth it or not, in next sample algorithm public void multiply(final double val) { final int rows = getSize1(); final int cols = getSize2(); for (int i = 0; i < rows; i++) { for (int j = 0; j < cols; j++) { this.get(i).set(j, this.get(i).get(j) * val); } } } My question is does changing double to Double makes a difference ? or that's a micro optimizing that won't affect anything ? keep in mind I might be using large matrices.2nd Should I consider redesigning the whole program again ?

    Read the article

  • [PHP] Does unsetting array values during iterating save on memory?

    - by saturn_rising
    Hello fellow code warriors, This is a simple programming question, coming from my lack of knowledge of how PHP handles array copying and unsetting during a foreach loop. It's like this, I have an array that comes to me from an outside source formatted in a way I want to change. A simple example would be: $myData = array('Key1' => array('value1', 'value2')); But what I want would be something like: $myData = array([0] => array('MyKey' => array('Key1' => array('value1', 'value2')))); So I take the first $myData and format it like the second $myData. I'm totally fine with my formatting algorithm. My question lies in finding a way to conserve memory since these arrays might get a little unwieldy. So, during my foreach loop I copy the current array value(s) into the new format, then I unset the value I'm working with from the original array. E.g.: $formattedData = array(); foreach ($myData as $key => $val) { // do some formatting here, copy to $reformattedVal $formattedData[] = $reformattedVal; unset($myData[$key]); } Is the call to unset() a good idea here? I.e., does it conserve memory since I have copied the data and no longer need the original value? Or, does PHP automatically garbage collect the data since I don't reference it in any subsequent code? The code runs fine, and so far my datasets have been too negligible in size to test for performance differences. I just don't know if I'm setting myself up for some weird bugs or CPU hits later on. Thanks for any insights. -sR

    Read the article

  • Is it OK to learn an algorithm from an open source project, and then implement it in a closed source project?

    - by Chris Barry
    Reference The post that started it all In order to clear up the original question I asked in a provocative manner, I have posed this question. If you learn an algorithm from an open source project, is it OK to use that algorithm in a separate closed sourced project? And if not, does that imply that you cannot use that knowledge ever again? If you can use it, what circumstance could that be? Just to clarify, I am not trying to evade a licence, otherwise I would not have asked the question in the first place. I believe this presents a difficult question and it is interesting to know where the debate can end up.

    Read the article

  • Is there an appropriate coding style for implementing an algorithm during an interview?

    - by GlenPeterson
    I failed an interview question in C years ago about converting hex to decimal by not exploiting the ASCII table if (inputDigitByte > 9) hex = inputDigitByte - 'a'. The rise of Unicode has made this question pretty silly, but the point was that the interviewer valued raw execution speed above readability and error handling. They tell you to review algorithms textbooks to prepare for these interviews, yet these same textbooks tend to favor the implementation with the fewest lines of code, even if it has to rely on magic numbers (like "infinity") and a slower, more memory-intensive implementation (like a linked list instead of an array) to do that. I don't know what is right. Coding an algorithm within the space of an interview has at least 3 constraints: time to code, elegance/readability, and efficiency of execution. What trade-offs are appropriate for interview code? How much do you follow the textbook definition of an algorithm? Is it better to eliminate recursion, unroll loops, and use arrays for efficiency? Or is it better to use recursion and special values like "infinity" or Integer.MAX_VALUE to reduce the number of lines of code needed to write the algorithm? Interface: Make a very self-contained, bullet-proof interface, or sloppy and fast? On the one extreme, the array to be sorted might be a public static variable. On the other extreme, it might need to be passed to each method, allowing methods to be called individually from different threads for different purposes. Is it appropriate to use a linked-list data structure for items that are traversed in one direction vs. using arrays and doubling the size when the array is full? Implementing a singly-linked list during the interview is often much faster to code and easier remember for recursive algorithms like MergeSort. Thread safety - just document that it's unsafe, or say so verbally? How much should the interviewee be looking for opportunities for parallel processing? Is bit shifting appropriate? x / 2 or x >> 1 Polymorphism, type safety, and generics? Comments? Variable and method names: qs(a, p, q, r) vs: quickSort(theArray, minIdx, partIdx, maxIdx) How much should you use existing APIs? Obviously you can't use a java.util.HashMap to implement a hash-table, but what about using a java.util.List to accumulate your sorted results? Are there any guiding principals that would answer these and other questions, or is the guiding principal to ask the interviewer? Or maybe this should be the basis of a discussion while writing the code? If an interviewer can't or won't answer one of these questions, are there any tips for coaxing the information out of them?

    Read the article

  • Solved: Chrome v18, self signed certs and &ldquo;signed using a weak signature algorithm&rdquo;

    - by David Christiansen
    So chrome has just updated itself automatically and you are now running v18 – great. Or is it… If like me, you are someone that are running sites using a self-signed SSL Certificate (i.e. when running a site on a developer machine) you may come across the following lovely message; Fear not, this is likely as a result of you following instructions you found on the apache openssl site which results in a self signed cert using the MD5 signature hashing algorithm. The simple fix is to generate a new certificate specifying to use the SHA1 signature hashing algorithm, like so; openssl req -new -x509 -sha1 -nodes -out server.crt -keyout server.key Simples!

    Read the article

  • Is there anything else I can do to optimize this MySQL query?

    - by Legend
    I have two tables, Table A with 700,000 entries and Table B with 600,000 entries. The structure is as follows: Table A: +-----------+---------------------+------+-----+---------+----------------+ | Field | Type | Null | Key | Default | Extra | +-----------+---------------------+------+-----+---------+----------------+ | id | bigint(20) unsigned | NO | PRI | NULL | auto_increment | | number | bigint(20) unsigned | YES | | NULL | | +-----------+---------------------+------+-----+---------+----------------+ Table B: +-------------+---------------------+------+-----+---------+----------------+ | Field | Type | Null | Key | Default | Extra | +-------------+---------------------+------+-----+---------+----------------+ | id | bigint(20) unsigned | NO | PRI | NULL | auto_increment | | number_s | bigint(20) unsigned | YES | MUL | NULL | | | number_e | bigint(20) unsigned | YES | MUL | NULL | | | source | varchar(50) | YES | | NULL | | +-------------+---------------------+------+-----+---------+----------------+ I am trying to find if any of the values in Table A are present in Table B using the following code: $sql = "SELECT number from TableA"; $result = mysql_query($sql) or die(mysql_error()); while($row = mysql_fetch_assoc($result)) { $number = $row['number']; $sql = "SELECT source, count(source) FROM TableB WHERE number_s < $number AND number_e > $number GROUP BY source"; $re = mysql_query($sql) or die(mysql_error); while($ro = mysql_fetch_array($re)) { echo $number."\t".$ro[0]."\t".$ro[1]."\n"; } } I was hoping that the query would go fast but then for some reason, it isn't terrible fast. My explain on the select (with a particular value of "number") gives me the following: mysql> explain SELECT source, count(source) FROM TableB WHERE number_s < 1812194440 AND number_e > 1812194440 GROUP BY source; +----+-------------+------------+------+-------------------------+------+---------+------+--------+----------------------------------------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+-------------+------------+------+-------------------------+------+---------+------+--------+----------------------------------------------+ | 1 | SIMPLE | TableB | ALL | number_s,number_e | NULL | NULL | NULL | 696325 | Using where; Using temporary; Using filesort | +----+-------------+------------+------+-------------------------+------+---------+------+--------+----------------------------------------------+ 1 row in set (0.00 sec) Is there any optimization that I can squeeze out of this? I tried writing a stored procedure for the same task but it doesn't even seem to work in the first place... It doesn't give any syntax errors... I tried running it for a day and it was still running which felt odd. CREATE PROCEDURE Filter() Begin DECLARE number BIGINT UNSIGNED; DECLARE x INT; DECLARE done INT DEFAULT 0; DECLARE cur1 CURSOR FOR SELECT number FROM TableA; DECLARE CONTINUE HANDLER FOR NOT FOUND SET done = 1; CREATE TEMPORARY TABLE IF NOT EXISTS Flags(number bigint unsigned, count int(11)); OPEN cur1; hist_loop: LOOP FETCH cur1 INTO number; SELECT count(*) from TableB WHERE number_s < number AND number_e > number INTO x; IF done = 1 THEN LEAVE hist_loop; END IF; IF x IS NOT NULL AND x>0 THEN INSERT INTO Flags(number, count) VALUES(number, x); END IF; END LOOP hist_loop; CLOSE cur1; END

    Read the article

  • Local Variables take 7x longer to access than global variables?

    - by ItzWarty
    I was trying to benchmark the gain/loss of "caching" math.floor, in hopes that I could make calls faster. Here was the test: <html> <head> <script> window.onload = function() { var startTime = new Date().getTime(); var k = 0; for(var i = 0; i < 1000000; i++) k += Math.floor(9.99); var mathFloorTime = new Date().getTime() - startTime; startTime = new Date().getTime(); window.mfloor = Math.floor; k = 0; for(var i = 0; i < 1000000; i++) k += window.mfloor(9.99); var globalFloorTime = new Date().getTime() - startTime; startTime = new Date().getTime(); var mfloor = Math.floor; k = 0; for(var i = 0; i < 1000000; i++) k += mfloor(9.99); var localFloorTime = new Date().getTime() - startTime; document.getElementById("MathResult").innerHTML = mathFloorTime; document.getElementById("globalResult").innerHTML = globalFloorTime; document.getElementById("localResult").innerHTML = localFloorTime; }; </script> </head> <body> Math.floor: <span id="MathResult"></span>ms <br /> var mathfloor: <span id="globalResult"></span>ms <br /> window.mathfloor: <span id="localResult"></span>ms <br /> </body> </html> My results from the test: [Chromium 5.0.308.0]: Math.floor: 49ms var mathfloor: 271ms window.mathfloor: 40ms [IE 8.0.6001.18702] Math.floor: 703ms var mathfloor: 9890ms [LOL!] window.mathfloor: 375ms [Firefox [Minefield] 3.7a4pre] Math.floor: 42ms var mathfloor: 2257ms window.mathfloor: 60ms [Safari 4.0.4[531.21.10] ] Math.floor: 92ms var mathfloor: 289ms window.mathfloor: 90ms [Opera 10.10 build 1893] Math.floor: 500ms var mathfloor: 843ms window.mathfloor: 360ms [Konqueror 4.3.90 [KDE 4.3.90 [KDE 4.4 RC1]]] Math.floor: 453ms var mathfloor: 563ms window.mathfloor: 312ms The variance is random, of course, but for the most part In all cases [this shows time taken]: [takes longer] mathfloor Math.floor window.mathfloor [is faster] Why is this? In my projects i've been using var mfloor = Math.floor, and according to my not-so-amazing benchmarks, my efforts to "optimize" actually slowed down the script by ALOT... Is there any other way to make my code more "efficient"...? I'm at the stage where i basically need to optimize, so no, this isn't "premature optimization"...

    Read the article

  • Changing html <-> ajax <-> php/mysql to threaded approach

    - by Saif Bechan
    I have an application that needs to be updated real-time. There are various counters and other information that have to come from the database and the system needs to be up to date for the user. My approach now is just a normal ajax request every second to get the new values from the database. There is a JavaScript which loops every second getting the values trough ajax. This works fine but I think its very inefficient. The problem There is an ajax script that loops every second requesting data from php # On the server it has to load the PHP interpeter The PHP file has to get the data and format it correctly # PHP has to make a connection with the mysql database Work with the database(reads,never writes) Format the data so it can be send Send the data back to the browser # Close the database connection, and close the php interpeter Last the browser has to read these values and update the various html parts Now with this approach it has to load the interpreter and make a db connection every second. I was thinking of a way to make this more efficient, and maybe use a threaded approach to this. Threaded aprouch Do a post to the PHP when you enter the page and keep the connection alive In PHP only load the interpreter once, and make a connection to the DB ones Every second send an ajax response to the javascript listener The javascript listener than just changes values as the response from php arrives. I think this approach will be a great optimization to the server load and overall performance. But I can spot some weak point in the system and i need some help with these. Problems with the approach PHP execution time limit I don't think PHP is designed for such a setup. I know there is a time limit on php script execution. I don't know if an everlasting loop in PHP will cause any serious cpu/memory problems. Sending ajax request without breaking I don't know if it is possible to have just one ajax post action and have open and accepting data. user exists the page What will happen when the user exists the page and the PHP script is still going. Will it go on forever. security issues so far i can't think of any security issues. Almost every setup you use have some security issues. Maybe there are some with this solution I do not know of. Open to other solution I really want to change the setup as it is now and move to a threaded approach or better. If someone has a better approach to tackle this I definitely want to hear that. Maybe the usage of some other scripts is better suited for having an ongoing runtime. I only know php and java so any suggestions are welcome and I am willing to dig trough. I know there are things like perl, python etcetera that are used for this type of threaded but i don't know which one is best suited. When using other script If the best way is to go with other type of script like perl,python etcetera I do have some critera. The script has to be accessible via ajax post If it accepts some kind of json encode/decode it would be nice The script has to be able to access the session file This is essential because I need to know if the user is logged in The script has to be able to easily talk to MySQL All comments are welcome, and I hope this question is helpful to other also. Cheers!

    Read the article

  • Can my loop be optimized any more? (C++)

    - by Sagekilla
    Below is one of my inner loops that's run several thousand times, with input sizes of 20 - 1000 or more. Is there anything I can do to help squeeze any more performance out of this? I'm not looking to move this code to something like using tree codes (Barnes-Hut), but towards optimizing the actual calculations happening inside, since the same calculations occur in the Barnes-Hut algorithm. Any help is appreciated! typedef double real; struct Particle { Vector pos, vel, acc, jerk; Vector oldPos, oldVel, oldAcc, oldJerk; real mass; }; class Vector { private: real vec[3]; public: // Operators defined here }; real Gravity::interact(Particle *p, size_t numParticles) { PROFILE_FUNC(); real tau_q = 1e300; for (size_t i = 0; i < numParticles; i++) { p[i].jerk = 0; p[i].acc = 0; } for (size_t i = 0; i < numParticles; i++) { for (size_t j = i+1; j < numParticles; j++) { Vector r = p[j].pos - p[i].pos; Vector v = p[j].vel - p[i].vel; real r2 = lengthsq(r); real v2 = lengthsq(v); // Calculate inverse of |r|^3 real r3i = Constants::G * pow(r2, -1.5); // da = r / |r|^3 // dj = (v / |r|^3 - 3 * (r . v) * r / |r|^5 Vector da = r * r3i; Vector dj = (v - r * (3 * dot(r, v) / r2)) * r3i; // Calculate new acceleration and jerk p[i].acc += da * p[j].mass; p[i].jerk += dj * p[j].mass; p[j].acc -= da * p[i].mass; p[j].jerk -= dj * p[i].mass; // Collision estimation // Metric 1) tau = |r|^2 / |a(j) - a(i)| // Metric 2) tau = |r|^4 / |v|^4 real mij = p[i].mass + p[j].mass; real tau_est_q1 = r2 / (lengthsq(da) * mij * mij); real tau_est_q2 = (r2*r2) / (v2*v2); if (tau_est_q1 < tau_q) tau_q = tau_est_q1; if (tau_est_q2 < tau_q) tau_q = tau_est_q2; } } return sqrt(sqrt(tau_q)); }

    Read the article

  • Why is processing a sorted array faster than an unsorted array?

    - by GManNickG
    Here is a piece of code that shows some very peculiar performance. For some strange reason, sorting the data miraculously speeds up the code by almost 6x: #include <algorithm> #include <ctime> #include <iostream> int main() { // generate data const unsigned arraySize = 32768; int data[arraySize]; for (unsigned c = 0; c < arraySize; ++c) data[c] = std::rand() % 256; // !!! with this, the next loop runs faster std::sort(data, data + arraySize); // test clock_t start = clock(); long long sum = 0; for (unsigned i = 0; i < 100000; ++i) { // primary loop for (unsigned c = 0; c < arraySize; ++c) { if (data[c] >= 128) sum += data[c]; } } double elapsedTime = static_cast<double>(clock() - start) / CLOCKS_PER_SEC; std::cout << elapsedTime << std::endl; std::cout << "sum = " << sum << std::endl; } Without std::sort(data, data + arraySize);, the code runs in 11.54 seconds. With the sorted data, the code runs in 1.93 seconds. Initially I thought this might be just a language or compiler anomaly. So I tried it Java... import java.util.Arrays; import java.util.Random; public class Main { public static void main(String[] args) { // generate data int arraySize = 32768; int data[] = new int[arraySize]; Random rnd = new Random(0); for (int c = 0; c < arraySize; ++c) data[c] = rnd.nextInt() % 256; // !!! with this, the next loop runs faster Arrays.sort(data); // test long start = System.nanoTime(); long sum = 0; for (int i = 0; i < 100000; ++i) { // primary loop for (int c = 0; c < arraySize; ++c) { if (data[c] >= 128) sum += data[c]; } } System.out.println((System.nanoTime() - start) / 1000000000.0); System.out.println("sum = " + sum); } } with a similar but less extreme result. My first thought was that sorting brings the data into cache, but my next thought was how silly that is because the array was just generated. What is going on? Why is a sorted array faster than an unsorted array? The code is summing up some independent terms, the order should not matter.

    Read the article

  • JavaScript Optimisation

    - by Jayie
    I am using JavaScript to work out all the combinations of badminton doubles matches from a given list of players. Each player teams up with everyone else. EG. If I have the following players a, b, c & d. Their combinations can be: a & b V c & d a & c V b & d a & d V b & c I am using the code below, which I wrote to do the job, but it's a little inefficient. It loops through the PLAYERS array 4 times finding every single combination (including impossible ones). It then sorts the game out into alphabetical order and stores it in the GAMES array if it doesn't already exist. I can then use the first half of the GAMES array to list all game combinations. The trouble is if I have any more than 8 players it runs really slowly because the combination growth is exponential. Does anyone know a better way or algorithm I could use? The more I think about it the more my brain hurts! var PLAYERS = ["a", "b", "c", "d", "e", "f", "g"]; var GAMES = []; var p1, p2, p3, p4, i1, i2, i3, i4, entry, found, i; var pos = 0; var TEAM1 = []; var TEAM2 = []; // loop through players 4 times to get all combinations for (i1 = 0; i1 < PLAYERS.length; i1++) { p1 = PLAYERS[i1]; for (i2 = 0; i2 < PLAYERS.length; i2++) { p2 = PLAYERS[i2]; for (i3 = 0; i3 < PLAYERS.length; i3++) { p3 = PLAYERS[i3]; for (i4 = 0; i4 < PLAYERS.length; i4++) { p4 = PLAYERS[i4]; if ((p1 != p2 && p1 != p3 && p1 != p4) && (p2 != p1 && p2 != p3 && p2 != p4) && (p3 != p1 && p3 != p2 && p3 != p4) && (p4 != p1 && p4 != p2 && p4 != p3)) { // sort teams into alphabetical order (so we can compare them easily later) TEAM1[0] = p1; TEAM1[1] = p2; TEAM2[0] = p3; TEAM2[1] = p4; TEAM1.sort(); TEAM2.sort(); // work out the game and search the array to see if it already exists entry = TEAM1[0] + " & " + TEAM1[1] + " v " + TEAM2[0] + " & " + TEAM2[1]; found = false; for (i=0; i < GAMES.length; i++) { if (entry == GAMES[i]) found = true; } // if the game is unique then store it if (!found) { GAMES[pos] = entry; document.write((pos+1) + ": " + GAMES[pos] + "<br>"); pos++; } } } } } } Thanks in advance. Jason.

    Read the article

  • Accessing local variable doesn't improve performance

    - by NicMagnier
    The short version Why is this code: var index = (Math.floor(y / scale) * img.width + Math.floor(x / scale)) * 4; More performant than this one? var index = Math.floor(ref_index) * 4; The long version This week, the author of Impact js published an article about some rendering issue: http://www.phoboslab.org/log/2012/09/drawing-pixels-is-hard In the article there was the source of a function to scale an image by accessing pixels in the canvas. I wanted to suggest some traditional ways to optimize this kind of code so that the scaling would be shorter at loading time. But after testing it my result was most of the time worst that the original function. Guessing this was the JavaScript engine that was doing some smart optimization I tried to understand a bit more what was going on so I did a bunch of test. But my results are quite confusing and I would need some help to understand what's going on. I have a test page here: http://www.mx981.com/stuff/resize_bench/test.html jsPerf: http://jsperf.com/local-variable-due-to-the-scope-lookup To start the test, click the picture and the results will appear in the console. There are three different versions: The original code: for( var y = 0; y < heightScaled; y++ ) { for( var x = 0; x < widthScaled; x++ ) { var index = (Math.floor(y / scale) * img.width + Math.floor(x / scale)) * 4; var indexScaled = (y * widthScaled + x) * 4; scaledPixels.data[ indexScaled ] = origPixels.data[ index ]; scaledPixels.data[ indexScaled+1 ] = origPixels.data[ index+1 ]; scaledPixels.data[ indexScaled+2 ] = origPixels.data[ index+2 ]; scaledPixels.data[ indexScaled+3 ] = origPixels.data[ index+3 ]; } } jsPerf: http://jsperf.com/so-accessing-local-variable-doesn-t-improve-performance One of my attempt to optimize it: var ref_index = 0; var ref_indexScaled = 0 var ref_step = 1 / scale; for( var y = 0; y < heightScaled; y++ ) { for( var x = 0; x < widthScaled; x++ ) { var index = Math.floor(ref_index) * 4; scaledPixels.data[ ref_indexScaled++ ] = origPixels.data[ index ]; scaledPixels.data[ ref_indexScaled++ ] = origPixels.data[ index+1 ]; scaledPixels.data[ ref_indexScaled++ ] = origPixels.data[ index+2 ]; scaledPixels.data[ ref_indexScaled++ ] = origPixels.data[ index+3 ]; ref_index+= ref_step; } } jsPerf: http://jsperf.com/so-accessing-local-variable-doesn-t-improve-performance The same optimized code but with recalculating the index variable each time (Hybrid) var ref_index = 0; var ref_indexScaled = 0 var ref_step = 1 / scale; for( var y = 0; y < heightScaled; y++ ) { for( var x = 0; x < widthScaled; x++ ) { var index = (Math.floor(y / scale) * img.width + Math.floor(x / scale)) * 4; scaledPixels.data[ ref_indexScaled++ ] = origPixels.data[ index ]; scaledPixels.data[ ref_indexScaled++ ] = origPixels.data[ index+1 ]; scaledPixels.data[ ref_indexScaled++ ] = origPixels.data[ index+2 ]; scaledPixels.data[ ref_indexScaled++ ] = origPixels.data[ index+3 ]; ref_index+= ref_step; } } jsPerf: http://jsperf.com/so-accessing-local-variable-doesn-t-improve-performance The only difference in the two last one is the calculation of the 'index' variable. And to my surprise the optimized version is slower in most browsers (except opera). Results of personal testing (not the jsPerf tests): Opera Original: 8668ms Optimized: 932ms Hybrid: 8696ms Chrome Original: 139ms Optimized: 145ms Hybrid: 136ms Safari Original: 433ms Optimized: 853ms Hybrid: 451ms Firefox Original: 343ms Optimized: 422ms Hybrid: 350ms After digging around, it seems an usual good practice is to access mainly local variable due to the scope lookup. Because The optimized version only call one local variable it should be faster that the Hybrid code which call multiple variable and object in addition to the various operation involved. So why the "optimized" version is slower? I thought that it might be because some JavaScript engine don't optimize the Optimized version because it is not hot enough but after using --trace-opt in chrome, it seems all version are properly compiled by V8. At this point I am a bit clueless and wonder if somebody would know what is going on? I did also some more test cases in this page: http://www.mx981.com/stuff/resize_bench/index.html

    Read the article

  • What approach to take for SIMD optimizations

    - by goldenmean
    Hi, I am trying to optimize below code for SIMD operations (8way/4way/2way SIMD whiechever possible and if it gives gains in performance) I am tryin to analyze it first on paper to understand the algorithm used. How can i optimize it for SIMD:- void idct(uint8_t *dst, int stride, int16_t *input, int type) { int16_t *ip = input; uint8_t *cm = ff_cropTbl + MAX_NEG_CROP; int A, B, C, D, Ad, Bd, Cd, Dd, E, F, G, H; int Ed, Gd, Add, Bdd, Fd, Hd; int i; /* Inverse DCT on the rows now */ for (i = 0; i < 8; i++) { /* Check for non-zero values */ if ( ip[0] | ip[1] | ip[2] | ip[3] | ip[4] | ip[5] | ip[6] | ip[7] ) { A = M(xC1S7, ip[1]) + M(xC7S1, ip[7]); B = M(xC7S1, ip[1]) - M(xC1S7, ip[7]); C = M(xC3S5, ip[3]) + M(xC5S3, ip[5]); D = M(xC3S5, ip[5]) - M(xC5S3, ip[3]); Ad = M(xC4S4, (A - C)); Bd = M(xC4S4, (B - D)); Cd = A + C; Dd = B + D; E = M(xC4S4, (ip[0] + ip[4])); F = M(xC4S4, (ip[0] - ip[4])); G = M(xC2S6, ip[2]) + M(xC6S2, ip[6]); H = M(xC6S2, ip[2]) - M(xC2S6, ip[6]); Ed = E - G; Gd = E + G; Add = F + Ad; Bdd = Bd - H; Fd = F - Ad; Hd = Bd + H; /* Final sequence of operations over-write original inputs. */ ip[0] = (int16_t)(Gd + Cd) ; ip[7] = (int16_t)(Gd - Cd ); ip[1] = (int16_t)(Add + Hd); ip[2] = (int16_t)(Add - Hd); ip[3] = (int16_t)(Ed + Dd) ; ip[4] = (int16_t)(Ed - Dd ); ip[5] = (int16_t)(Fd + Bdd); ip[6] = (int16_t)(Fd - Bdd); } ip += 8; /* next row */ } ip = input; for ( i = 0; i < 8; i++) { /* Check for non-zero values (bitwise or faster than ||) */ if ( ip[1 * 8] | ip[2 * 8] | ip[3 * 8] | ip[4 * 8] | ip[5 * 8] | ip[6 * 8] | ip[7 * 8] ) { A = M(xC1S7, ip[1*8]) + M(xC7S1, ip[7*8]); B = M(xC7S1, ip[1*8]) - M(xC1S7, ip[7*8]); C = M(xC3S5, ip[3*8]) + M(xC5S3, ip[5*8]); D = M(xC3S5, ip[5*8]) - M(xC5S3, ip[3*8]); Ad = M(xC4S4, (A - C)); Bd = M(xC4S4, (B - D)); Cd = A + C; Dd = B + D; E = M(xC4S4, (ip[0*8] + ip[4*8])) + 8; F = M(xC4S4, (ip[0*8] - ip[4*8])) + 8; if(type==1){ //HACK E += 16*128; F += 16*128; } G = M(xC2S6, ip[2*8]) + M(xC6S2, ip[6*8]); H = M(xC6S2, ip[2*8]) - M(xC2S6, ip[6*8]); Ed = E - G; Gd = E + G; Add = F + Ad; Bdd = Bd - H; Fd = F - Ad; Hd = Bd + H; /* Final sequence of operations over-write original inputs. */ if(type==0){ ip[0*8] = (int16_t)((Gd + Cd ) >> 4); ip[7*8] = (int16_t)((Gd - Cd ) >> 4); ip[1*8] = (int16_t)((Add + Hd ) >> 4); ip[2*8] = (int16_t)((Add - Hd ) >> 4); ip[3*8] = (int16_t)((Ed + Dd ) >> 4); ip[4*8] = (int16_t)((Ed - Dd ) >> 4); ip[5*8] = (int16_t)((Fd + Bdd ) >> 4); ip[6*8] = (int16_t)((Fd - Bdd ) >> 4); }else if(type==1){ dst[0*stride] = cm[(Gd + Cd ) >> 4]; dst[7*stride] = cm[(Gd - Cd ) >> 4]; dst[1*stride] = cm[(Add + Hd ) >> 4]; dst[2*stride] = cm[(Add - Hd ) >> 4]; dst[3*stride] = cm[(Ed + Dd ) >> 4]; dst[4*stride] = cm[(Ed - Dd ) >> 4]; dst[5*stride] = cm[(Fd + Bdd ) >> 4]; dst[6*stride] = cm[(Fd - Bdd ) >> 4]; }else{ dst[0*stride] = cm[dst[0*stride] + ((Gd + Cd ) >> 4)]; dst[7*stride] = cm[dst[7*stride] + ((Gd - Cd ) >> 4)]; dst[1*stride] = cm[dst[1*stride] + ((Add + Hd ) >> 4)]; dst[2*stride] = cm[dst[2*stride] + ((Add - Hd ) >> 4)]; dst[3*stride] = cm[dst[3*stride] + ((Ed + Dd ) >> 4)]; dst[4*stride] = cm[dst[4*stride] + ((Ed - Dd ) >> 4)]; dst[5*stride] = cm[dst[5*stride] + ((Fd + Bdd ) >> 4)]; dst[6*stride] = cm[dst[6*stride] + ((Fd - Bdd ) >> 4)]; } } else { if(type==0){ ip[0*8] = ip[1*8] = ip[2*8] = ip[3*8] = ip[4*8] = ip[5*8] = ip[6*8] = ip[7*8] = ((xC4S4 * ip[0*8] + (IdctAdjustBeforeShift<<16))>>20); }else if(type==1){ dst[0*stride]= dst[1*stride]= dst[2*stride]= dst[3*stride]= dst[4*stride]= dst[5*stride]= dst[6*stride]= dst[7*stride]= cm[128 + ((xC4S4 * ip[0*8] + (IdctAdjustBeforeShift<<16))>>20)]; }else{ if(ip[0*8]){ int v= ((xC4S4 * ip[0*8] + (IdctAdjustBeforeShift<<16))>>20); dst[0*stride] = cm[dst[0*stride] + v]; dst[1*stride] = cm[dst[1*stride] + v]; dst[2*stride] = cm[dst[2*stride] + v]; dst[3*stride] = cm[dst[3*stride] + v]; dst[4*stride] = cm[dst[4*stride] + v]; dst[5*stride] = cm[dst[5*stride] + v]; dst[6*stride] = cm[dst[6*stride] + v]; dst[7*stride] = cm[dst[7*stride] + v]; } } } ip++; /* next column */ dst++; } }

    Read the article

  • Optimizing sorting container of objects with heap-allocated buffers - how to avoid hard-copying buff

    - by Kache4
    I was making sure I knew how to do the op= and copy constructor correctly in order to sort() properly, so I wrote up a test case. After getting it to work, I realized that the op= was hard-copying all the data_. I figure if I wanted to sort a container with this structure (its elements have heap allocated char buffer arrays), it'd be faster to just swap the pointers around. Is there a way to do that? Would I have to write my own sort/swap function? #include <deque> //#include <string> //#include <utility> //#include <cstdlib> #include <cstring> #include <iostream> //#include <algorithm> // I use sort(), so why does this still compile when commented out? #include <boost/filesystem.hpp> #include <boost/foreach.hpp> using namespace std; namespace fs = boost::filesystem; class Page { public: // constructor Page(const char* path, const char* data, int size) : path_(fs::path(path)), size_(size), data_(new char[size]) { // cout << "Creating Page..." << endl; strncpy(data_, data, size); // cout << "done creating Page..." << endl; } // copy constructor Page(const Page& other) : path_(fs::path(other.path())), size_(other.size()), data_(new char[other.size()]) { // cout << "Copying Page..." << endl; strncpy(data_, other.data(), size_); // cout << "done copying Page..." << endl; } // destructor ~Page() { delete[] data_; } // accessors const fs::path& path() const { return path_; } const char* data() const { return data_; } int size() const { return size_; } // operators Page& operator = (const Page& other) { if (this == &other) return *this; char* newImage = new char[other.size()]; strncpy(newImage, other.data(), other.size()); delete[] data_; data_ = newImage; path_ = fs::path(other.path()); size_ = other.size(); return *this; } bool operator < (const Page& other) const { return path_ < other.path(); } private: fs::path path_; int size_; char* data_; }; class Book { public: Book(const char* path) : path_(fs::path(path)) { cout << "Creating Book..." << endl; cout << "pushing back #1" << endl; pages_.push_back(Page("image1.jpg", "firstImageData", 14)); cout << "pushing back #3" << endl; pages_.push_back(Page("image3.jpg", "thirdImageData", 14)); cout << "pushing back #2" << endl; pages_.push_back(Page("image2.jpg", "secondImageData", 15)); cout << "testing operator <" << endl; cout << pages_[0].path().string() << (pages_[0] < pages_[1]? " < " : " > ") << pages_[1].path().string() << endl; cout << pages_[1].path().string() << (pages_[1] < pages_[2]? " < " : " > ") << pages_[2].path().string() << endl; cout << pages_[0].path().string() << (pages_[0] < pages_[2]? " < " : " > ") << pages_[2].path().string() << endl; cout << "sorting" << endl; BOOST_FOREACH (Page p, pages_) cout << p.path().string() << endl; sort(pages_.begin(), pages_.end()); cout << "done sorting\n"; BOOST_FOREACH (Page p, pages_) cout << p.path().string() << endl; cout << "checking datas" << endl; BOOST_FOREACH (Page p, pages_) { char data[p.size() + 1]; strncpy((char*)&data, p.data(), p.size()); data[p.size()] = '\0'; cout << p.path().string() << " " << data << endl; } cout << "done Creating Book" << endl; } private: deque<Page> pages_; fs::path path_; }; int main() { Book* book = new Book("/some/path/"); }

    Read the article

  • Idea of an algorithm to detect a website's navigation structure?

    - by Uwe Keim
    Currently I am in the process of developing an importer of any existing, arbitrary (static) HTML website into the upcoming release of our CMS. While the downloading the files is solved successfully, I'm pulling my hair off when it comes to detect a site structure (pages and subpages) purely from the HTML files, without the user specifying additional hints. Basically I want to get a tree like: + Root page 1 + Child page 1 + Child page 2 + Child child page1 + Child page 3 + Root page 2 + Child page 4 + Root page 3 + ... I.e. I want to be able to detect the menu structure from the links inside the pages. This has not to be 100% accurate, but at least I want to achieve more than just a flat list. I thought of looking at multiple pages to see similar areas and identify these as menu areas and parse the links there, but after all I'm not that satisfied with this idea. My question: Can you imagine any algorithm when it comes to detecting such a structure? Update 1: What I'm looking for is not a web spider, but an algorithm do create a logical tree of the relationship of the pages to be able to create pages and subpages inside my CMS when importing them. Update 2: As of Robert's suggestion I'll solve this by starting at the root page, and then simply parse links as you go and treat every link inside a page simply as a child page. Probably I'll recurse not in a deep-first manner but rather in a breadth-first manner to get a more balanced navigation structure.

    Read the article

  • Algorithm to measure how "diffused" 5,000 pennies are in an economy?

    - by makerofthings7
    Please allow me to use this example/metaphor to describe an algorithm I need. Objects There are 5 thousand pennies. There are 50 cups. There is a tracking history (Passport "stamp" etc) that is associated with each penny as it moves between cups. Definition I'll define a "highly diffused" penny as one that passes through many cups. A "poorly diffused" penny is one that either passes back and forth between 2 cups Question How can I objectively measure the diffusion of a penny as: The number of moves the penny has gone through The number of cups the penny has been in A unit of time (day, week, month) Why am I doing this? I want to detect if a cup is hoarding pennies. Resistance from bad actors Since hoarding is bad, the "bad cup" may simply solicit a partner and simply move pennies between each other. This will reduce the amount of time a coin isn't in transit, and would skew hoarding detection. A solution might be to detect if a cup (or set of cups) are common "partners" with each other, though I'm not sure how to think though this problem. Broad applicability Any assistance would be helpful, since I would think that this algorithm is common to Economics The study of migration patterns of animals, citizens of a country Other natural occurring phenomena ... and probably exists as a term or concept I'm unfamiliar with.

    Read the article

  • What's a good algorithm for a random, uneven distribution of a fixed amount of a resource?

    - by NickC
    Problem I have X, a positive integer, of some resource, R. There are N potential targets. I want to distribute all of R to the N targets in some "interesting" way. "Interesting" means: Some targets may not get any R. It should rarely be near even (with a majority of target getting near X/N of the resource). There should be at least a small chance of one target getting all of R. Bad solutions The naive approach would be to pick a random target and give one R to it and repeat X times. This would result in too even of an approach. The next idea is to pick a random number between 1 and X and give it to a random target. This results in too large of a number (at least X/2 on average) being given to one target. Question This algorithm will be used frequently and I want the distribution to be interesting and uneven so that the surprise doesn't wear off for users. Is there a good algorithm for something in between these two approaches, that fits the definition of interesting above?

    Read the article

  • What is Search Engine Optimization - An Art Or Science?

    As ridiculous and as outrageous as this question might sound, there has been no evident and obvious answer to this. The fact that the process of Search Engine optimization is an art or mere science is something that web scholars have been debating for a long time, and to people's amusement, have still not come to a concrete conclusion. One important step that was taken towards having this question answered or finding an answer to it was asking all the service providers about the way they think of SEO.

    Read the article

  • Search Engine Optimization and SEO Services - What Do They Offer?

    Search engine optimization involves using the Internet as a marketing tool. Companies that are using the Internet to attract customers desire to optimize their exposure to potential to customers. In order to best advantage of SEO, it is recommended that you hire a professional service that can implement programs to evaluate the optimum marketing potential of the Internet. When considering hiring a company to assist you in this process it is important to understand how such services work.

    Read the article

facebook twitter digg google delicious technorati stumbleupon myspace wordpress linkedin gmail igoogle windows live tumblr viadeo yahoo buzz yahoo mail yahoo bookmarks favorites email print

< Previous Page | 144 145 146 147 148 149 150 151 152 153 154 155  | Next Page >