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  • Creating and appending a big DOM with javascript - most optimized way?

    - by fenderplayer
    I use the following code to append a big dom on a mobile browser (webkit): 1. while(someIndex--) // someIndex ranges from 10 to possibly 1000 2. { 3. var html01 = ['<div class="test">', someVal,'</div>', 4. '<div><p>', someTxt.txt1, someTxt.txt2, '</p></div>', 5. // lots of html snippets interspersed with variables 6. // on average ~40 to 50 elements in this array 7. ].join(''); 8. var fragment = document.createDocumentFragment(), 9. div = fragment.appendChild(document.createElement('div')); 10. div.appendChild(jQuery(html01)[0]); 11. jQuery('#screen1').append(fragment); 12. } //end while loop 13. // similarly i create 'html02' till 'html15' to append in other screen divs Is there a better or faster way to do the above? Do you see any problems with the code? I am a little worried about line 10 where i wrap in jquery and then take it out.

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  • Using Memcached in Python/Django - questions.

    - by Thomas
    I am starting use Memcached to make my website faster. For constant data in my database I use this: from django.core.cache import cache cache_key = 'regions' regions = cache.get(cache_key) if result is None: """Not Found in Cache""" regions = Regions.objects.all() cache.set(cache_key, regions, 2592000) #(2592000sekund = 30 dni) return regions For seldom changed data I use signals: from django.core.cache import cache from django.db.models import signals def nuke_social_network_cache(self, instance, **kwargs): cache_key = 'networks_for_%s' % (self.instance.user_id,) cache.delete(cache_key) signals.post_save.connect(nuke_social_network_cache, sender=SocialNetworkProfile) signals.post_delete.connect(nuke_social_network_cache, sender=SocialNetworkProfile) Is it correct way? I installed django-memcached-0.1.2, which show me: Memcached Server Stats Server Keys Hits Gets Hit_Rate Traffic_In Traffic_Out Usage Uptime 127.0.0.1 15 220 276 79% 83.1 KB 364.1 KB 18.4 KB 22:21:25 Can sombody explain what columns means? And last question. I have templates where I am getting much records from a few table (relationships). So in my view I get records from one table and in templates show it and related info from others. Generating page last a few seconds for very small table (<100records). Is it some easy way to cache queries from templates? Have I to do some big structure in my view (with all related tables), cache it and send to template?

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  • What is the optimum way to select the most dissimilar individuals from a population?

    - by Aaron D
    I have tried to use k-means clustering to select the most diverse markers in my population, for example, if we want to select 100 lines I cluster the whole population to 100 clusters then select the closest marker to the centroid from each cluster. The problem with my solution is it takes too much time (probably my function needs optimization), especially when the number of markers exceeds 100000. So, I will appreciate it so much if anyone can show me a new way to select markers that maximize diversity in my population and/or help me optimize my function to make it work faster. Thank you # example: library(BLR) data(wheat) dim(X) mdf<-mostdiff(t(X), 100,1,nstart=1000) Here is the mostdiff function that i used: mostdiff <- function(markers, nClust, nMrkPerClust, nstart=1000) { transposedMarkers <- as.array(markers) mrkClust <- kmeans(transposedMarkers, nClust, nstart=nstart) save(mrkClust, file="markerCluster.Rdata") # within clusters, pick the markers that are closest to the cluster centroid # turn the vector of which markers belong to which clusters into a list nClust long # each element of the list is a vector of the markers in that cluster clustersToList <- function(nClust, clusters) { vecOfCluster <- function(whichClust, clusters) { return(which(whichClust == clusters)) } return(apply(as.array(1:nClust), 1, vecOfCluster, clusters)) } pickCloseToCenter <- function(vecOfCluster, whichClust, transposedMarkers, centers, pickHowMany) { clustSize <- length(vecOfCluster) # if there are fewer than three markers, the center is equally distant from all so don't bother if (clustSize < 3) return(vecOfCluster[1:min(pickHowMany, clustSize)]) # figure out the distance (squared) between each marker in the cluster and the cluster center distToCenter <- function(marker, center){ diff <- center - marker return(sum(diff*diff)) } dists <- apply(transposedMarkers[vecOfCluster,], 1, distToCenter, center=centers[whichClust,]) return(vecOfCluster[order(dists)[1:min(pickHowMany, clustSize)]]) } }

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  • JQuery with css3 keydown keyCode = 37 and 39

    - by rayrule
    I have tested both ways. jquery animation and css3 transition, and css3 is a little bit faster. But i have a problem with the following code: $(document).keydown(function(e){ if (e.keyCode == 39) { var DocHeight = $(document).height(); $('.container').css("margin-top","-="+DocHeight) } }); if i hit twice on keyCode 39 (arrow to the right) than my transition is outer space. Does anyone has an solution for this thing? outer space maybe not the correct word. But the problem is. if i hit twice the arrow key i'll get the last request, in other words... animation is started, and another animation start from the position that i don't want. example: hit #1 margin-top is at 0px and goes to 1024px. but when i hit it twice the margin-top is at 23px, and it stops at 1047px. This is not what i want. It has to stop at 1024px. I hope so.

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  • Multithreaded linked list traversal

    - by Rob Bryce
    Given a (doubly) linked list of objects (C++), I have an operation that I would like multithread, to perform on each object. The cost of the operation is not uniform for each object. The linked list is the preferred storage for this set of objects for a variety of reasons. The 1st element in each object is the pointer to the next object; the 2nd element is the previous object in the list. I have solved the problem by building an array of nodes, and applying OpenMP. This gave decent performance. I then switched to my own threading routines (based off Windows primitives) and by using InterlockedIncrement() (acting on the index into the array), I can achieve higher overall CPU utilization and faster through-put. Essentially, the threads work by "leap-frog'ing" along the elements. My next approach to optimization is to try to eliminate creating/reusing the array of elements in my linked list. However, I'd like to continue with this "leap-frog" approach and somehow use some nonexistent routine that could be called "InterlockedCompareDereference" - to atomically compare against NULL (end of list) and conditionally dereference & store, returning the dereferenced value. I don't think InterlockedCompareExchangePointer() will work since I cannot atomically dereference the pointer and call this Interlocked() method. I've done some reading and others are suggesting critical sections or spin-locks. Critical sections seem heavy-weight here. I'm tempted to try spin-locks but I thought I'd first pose the question here and ask what other people are doing. I'm not convinced that the InterlockedCompareExchangePointer() method itself could be used like a spin-lock. Then one also has to consider acquire/release/fence semantics... Ideas? Thanks!

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  • Simple question about the lunarlander example.

    - by Smills
    I am basing my game off the lunarlander example. This is the run loop I am using (very similar to what is used in lunarlander). I am getting considerable performance issues associated with my drawing, even if I draw almost nothing. I noticed the below method. Why is the canvas being created and set to null each cycle? @Override public void run() { while (mRun) { Canvas c = null; try { c = mSurfaceHolder.lockCanvas();//null synchronized (mSurfaceHolder) { updatePhysics(); doDraw(c); } } finally { // do this in a finally so that if an exception is thrown // during the above, we don't leave the Surface in an // inconsistent state if (c != null) { mSurfaceHolder.unlockCanvasAndPost(c); } } } } Most of the times I have read anything about canvases it is more along the lines of: mField = new Bitmap(...dimensions...); Canvas c = new Canvas(mField); My question is: why is Google's example done that way (null canvas), what are the benefits of this, and is there a faster way to do it?

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  • cross-platform development for mobile devices

    - by user924
    What language/framework is best worth learning for mobile application development? My specific situation is that I'm very familiar with Java and C++ (I especially love Qt), but have limited experience with other languages. Some options I'm considering: 1) Learn Objective-C and all the iPhone-specific tools I do have access to a mac. The downside here is I'm restricted to the iPhone, so I'd have to rewrite almost everything if I wanted to branch off into another mobile device (or move later to a cross-platform framework). Even after knowing Objective-C, it seems like other frameworks might be more efficient/faster to code in? 2) Use some existing cross-platform framework for development I've looked at rhomobile, but I only have limited experience with Ruby (and at first glance, it might be a little pricey comapred to other options). Appcelerator also looks popular and nice, but it uses html/css/javascript. Airplaysdk looks good, but it's new and I haven't been able to see much written about it (is it worth going for?). 3) Wait for something better to come along How far away is Qt for the iPhone? That would be ideal, but it isn't available now. So what do you recommend? Productivity/efficiency is my top priority, although learning a useful language for the long term would also be okay. Thanks

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  • Protecting my apps security from deassembling

    - by sandis
    So I recently tested deassembling one of my android apps, and to my horror I discovered that the code was quite readable. Even worse, all my variable names where intact! I thought that those would be compressed to something unreadable at compile time. The app is triggered to expire after a certain time. However, now it was trivial for me to find my function named checkIfExpired() and find the variable "expired". Is there any good way of making it harder for a potential hacker messing with my app? Before someone states the obvious: Yes, it is security through obscurity. But obviously this is my only option since the user always will have access to all my code. This is the same for all apps. The details of my deactivation-thingy is unimportant, the point is that I dont want deassembler to understand some of the things I do. side questions: Why are the variable names not compressed? Could it be the case that my program would run faster if I stopped using really long variable names, as are my habit?

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  • Currently using View, Should I use a hard table instead?

    - by 1001010101
    I am currently debating whether my table, mapping_uGroups_uProducts, which is a view formed by the following table: CREATE ALGORITHM=UNDEFINED DEFINER=`root`@`localhost` SQL SECURITY DEFINER VIEW `db`.`mapping_uGroups_uProducts` AS select distinct `X`.`upID` AS `upID`,`Z`.`ugID` AS `ugID` from ((`db`.`mapping_uProducts_Products` `X` join `db`.`productsInfo` `Y` on((`X`.`pID` = `Y`.`pID`))) join `db`.`mapping_uGroups_Groups` `Z` on((`Y`.`gID` = `Z`.`gID`))); My current query is: SELECT upID FROM uProductsInfo \ JOIN fs_uProducts USING (upID) column \ JOIN mapping_uGroups_uProducts USING (upID) -- could be faster if we use hard table and index \ JOIN mapping_fs_key USING (fsKeyID) \ WHERE fsName="OVERALL" \ AND ugID=1 \ ORDER BY score DESC \ LIMIT 0,30; which is pretty slow. (for 30 results, it requires about 10 secondes). I think the reason for my query being so slow is definitely due to the fact that that particular query relies on a VIEW which has no index to speed things up. +----+-------------+----------------+--------+----------------+---------+---------+---------------------------------------+-------+---------------------------------+ | id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra | +----+-------------+----------------+--------+----------------+---------+---------+---------------------------------------+-------+---------------------------------+ | 1 | PRIMARY | mapping_fs_key | const | PRIMARY,fsName | fsName | 386 | const | 1 | Using temporary; Using filesort | | 1 | PRIMARY | <derived2> | ALL | NULL | NULL | NULL | NULL | 19706 | Using where | | 1 | PRIMARY | uProductsInfo | eq_ref | PRIMARY | PRIMARY | 4 | mapping_uGroups_uProducts.upID | 1 | Using index | | 1 | PRIMARY | fs_uProducts | ref | upID | upID | 4 | db.uProductsInfo.upID | 221 | Using where | | 2 | DERIVED | X | ALL | PRIMARY | NULL | NULL | NULL | 40772 | Using temporary | | 2 | DERIVED | Y | eq_ref | PRIMARY | PRIMARY | 4 | db.X.pID | 1 | Distinct | | 2 | DERIVED | Z | ref | PRIMARY | PRIMARY | 4 | db.Y.gID | 2 | Using index; Distinct | +----+-------------+----------------+--------+----------------+---------+---------+---------------------------------------+-------+---------------------------------+ 7 rows in set (0.48 sec) The explain here looks pretty cryptic, and I don't know whether I should drop view and write a script to just insert everything in the view to a hard table. ( obviously, it will lose the flexibility of the view since the mapping changes quite frequently). Does anyone have any idea to how I can optimize my schema better?

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  • Creating an object in the loop

    - by Jacob
    std::vector<double> C(4); for(int i = 0; i < 1000;++i) for(int j = 0; j < 2000; ++j) { C[0] = 1.0; C[1] = 1.0; C[2] = 1.0; C[3] = 1.0; } is much faster than for(int i = 0; i < 1000;++i) for(int j = 0; j < 2000; ++j) { std::vector<double> C(4); C[0] = 1.0; C[1] = 1.0; C[2] = 1.0; C[3] = 1.0; } I realize this happens because std::vector is repeatedly being created and instantiated in the loop, but I was under the impression this would be optimized away. Is it completely wrong to keep variables local in a loop whenever possible? I was under the (perhaps false) impression that this would provide optimization opportunities for the compiler. EDIT: I use VC++2005 (release mode) with full optimization (/Ox)

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  • Slightly different execution times between python2 and python3

    - by user557634
    Hi. Lastly I wrote a simple generator of permutations in python (implementation of "plain changes" algorithm described by Knuth in "The Art... 4"). I was curious about the differences in execution time of it between python2 and python3. Here is my function: def perms(s): s = tuple(s) N = len(s) if N <= 1: yield s[:] raise StopIteration() for x in perms(s[1:]): for i in range(0,N): yield x[:i] + (s[0],) + x[i:] I tested both using timeit module. My tests: $ echo "python2.6:" && ./testing.py && echo "python3:" && ./testing3.py python2.6: args time[ms] 1 0.003811 2 0.008268 3 0.015907 4 0.042646 5 0.166755 6 0.908796 7 6.117996 8 48.346996 9 433.928967 10 4379.904032 python3: args time[ms] 1 0.00246778964996 2 0.00656183719635 3 0.01419159912 4 0.0406293644678 5 0.165960511097 6 0.923101452814 7 6.24257639835 8 53.0099868774 9 454.540967941 10 4585.83498001 As you can see, for number of arguments less than 6, python 3 is faster, but then roles are reversed and python2.6 does better. As I am a novice in python programming, I wonder why is that so? Or maybe my script is more optimized for python2? Thank you in advance for kind answer :)

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  • g-wan - reproducing the performance claims

    - by user2603628
    Using gwan_linux64-bit.tar.bz2 under Ubuntu 12.04 LTS unpacking and running gwan then pointing wrk at it (using a null file null.html) wrk --timeout 10 -t 2 -c 100 -d20s http://127.0.0.1:8080/null.html Running 20s test @ http://127.0.0.1:8080/null.html 2 threads and 100 connections Thread Stats Avg Stdev Max +/- Stdev Latency 11.65s 5.10s 13.89s 83.91% Req/Sec 3.33k 3.65k 12.33k 75.19% 125067 requests in 20.01s, 32.08MB read Socket errors: connect 0, read 37, write 0, timeout 49 Requests/sec: 6251.46 Transfer/sec: 1.60MB .. very poor performance, in fact there seems to be some kind of huge latency issue. During the test gwan is 200% busy and wrk is 67% busy. Pointing at nginx, wrk is 200% busy and nginx is 45% busy: wrk --timeout 10 -t 2 -c 100 -d20s http://127.0.0.1/null.html Thread Stats Avg Stdev Max +/- Stdev Latency 371.81us 134.05us 24.04ms 91.26% Req/Sec 72.75k 7.38k 109.22k 68.21% 2740883 requests in 20.00s, 540.95MB read Requests/sec: 137046.70 Transfer/sec: 27.05MB Pointing weighttpd at nginx gives even faster results: /usr/local/bin/weighttp -k -n 2000000 -c 500 -t 3 http://127.0.0.1/null.html weighttp - a lightweight and simple webserver benchmarking tool starting benchmark... spawning thread #1: 167 concurrent requests, 666667 total requests spawning thread #2: 167 concurrent requests, 666667 total requests spawning thread #3: 166 concurrent requests, 666666 total requests progress: 9% done progress: 19% done progress: 29% done progress: 39% done progress: 49% done progress: 59% done progress: 69% done progress: 79% done progress: 89% done progress: 99% done finished in 7 sec, 13 millisec and 293 microsec, 285172 req/s, 57633 kbyte/s requests: 2000000 total, 2000000 started, 2000000 done, 2000000 succeeded, 0 failed, 0 errored status codes: 2000000 2xx, 0 3xx, 0 4xx, 0 5xx traffic: 413901205 bytes total, 413901205 bytes http, 0 bytes data The server is a virtual 8 core dedicated server (bare metal), under KVM Where do I start looking to identify the problem gwan is having on this platform ? I have tested lighttpd, nginx and node.js on this same OS, and the results are all as one would expect. The server has been tuned in the usual way with expanded ephemeral ports, increased ulimits, adjusted time wait recycling etc.

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  • finding N contiguous zero bits in an integer to the left of the MSB from another

    - by James Morris
    First we find the MSB of the first integer, and then try to find a region of N contiguous zero bits within the second number which is to the left of the MSB from the first integer. Here is the C code for my solution: typedef unsigned int t; unsigned const t_bits = sizeof(t) * CHAR_BIT; _Bool test_fit_within_left_of_msb( unsigned width, t val1, t val2, unsigned* offset_result) { unsigned offbit = 0; unsigned msb = 0; t mask; t b; while(val1 >>= 1) ++msb; while(offbit + width < t_bits - msb) { mask = (((t)1 << width) - 1) << (t_bits - width - offbit); b = val2 & mask; if (!b) { *offset_result = offbit; return true; } if (offbit++) /* this conditional bothers me! */ b <<= offbit - 1; while(b <<= 1) offbit++; } return false; } Aside from faster ways of finding the MSB of the first integer, the commented test for a zero offbit seems a bit extraneous, but necessary to skip the highest bit of type t if it is set. I have also implemented similar algorithms but working to the right of the MSB of the first number, so they don't require this seemingly extra condition. How can I get rid of this extra condition, or even, are there far more optimal solutions?

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  • F# ref-mutable vars vs object fields

    - by rwallace
    I'm writing a parser in F#, and it needs to be as fast as possible (I'm hoping to parse a 100 MB file in less than a minute). As normal, it uses mutable variables to store the next available character and the next available token (i.e. both the lexer and the parser proper use one unit of lookahead). My current partial implementation uses local variables for these. Since closure variables can't be mutable (anyone know the reason for this?) I've declared them as ref: let rec read file includepath = let c = ref ' ' let k = ref NONE let sb = new StringBuilder() use stream = File.OpenText file let readc() = c := stream.Read() |> char // etc I assume this has some overhead (not much, I know, but I'm trying for maximum speed here), and it's a little inelegant. The most obvious alternative would be to create a parser class object and have the mutable variables be fields in it. Does anyone know which is likely to be faster? Is there any consensus on which is considered better/more idiomatic style? Is there another option I'm missing?

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  • Listening UDP or switch to TCP in a MFC application

    - by Alexander.S
    I'm editing a legacy MFC application, and I have to add some basic network functionalities. The operating side has to receive a simple instruction (numbers 1,2,3,4...) and do something based on that. The clients wants the latency to be as fast as possible, so naturally I decided to use datagrams (UDP). But reading all sorts of resources left me bugged. I cannot listen to UDP sockets (CAsyncSocket) in MFC, it's only possible to call Receive which blocks and waits. Blocking the UI isn't really a smart. So I guess I could use some threading technique, but since I'm not all that experienced with MFC how should that be implemented? The other part of the question is should I do this, or revert to TCP, considering reliability and implementation issues. I know that UDP is unreliable, but just how unreliable is it really? I read that it is up to 50% faster, which is a lot for me. References I used: http://msdn.microsoft.com/en-us/library/09dd1ycd(v=vs.80).aspx

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  • Jquery Mobile app focus-based navigation stops working after switching between pages

    - by nawar
    As much as I would like to expand on the details here, I am not able to find relevant information about the root cause of this problem. I am having this issue with my blackberry Webapp which I built using JQM. After few times of navigation from page to page, the application becomes unresponsive on the destination page and I am not able to scroll up/down using the touchpad. If someone had this problem or some clue to the resolution, then that would be helpful. Edit: after doing some research I was able to narrow down the cause of the issue. I am having an issue with focus-based navigation. As I lose focus on the page elements (buttons, input fields, etc) after few transitions among the pages. Edit I had to switch back to the cursor based navigation as it is much faster and do not have the issue faced by focus-based navigation. I removed the entry: <rim:navigation mode=”focus”/> from the config.xml file I found this entry on the blackberry fourms but it haven't solved my problem despite the fact I upgraded my WebWorks SDK to 2.0 from 1.5 http://supportforums.blackberry.com/t5/Web-and-WebWorks-Development/Focus-based-navigation-hangs-device/td-p/455600 Thanks

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  • Batch insert mode with hibernate and oracle: seems to be dropping back to slow mode silently

    - by Chris
    I'm trying to get a batch insert working with Hibernate into Oracle, according to what i've read here: http://docs.jboss.org/hibernate/core/3.3/reference/en/html/batch.html , but with my benchmarking it doesn't seem any faster than before. Can anyone suggest a way to prove whether hibernate is using batch mode or not? I hear that there are numerous reasons why it may silently drop into normal mode (eg associations and generated ids) so is there some way to find out why it has gone non-batch? My hibernate.cfg.xml contains this line which i believe is all i need to enable batch mode: <property name="jdbc.batch_size">50</property> My insert code looks like this: List<LogEntry> entries = ..a list of 100 LogEntry data classes... Session sess = sessionFactory.getCurrentSession(); for(LogEntry e : entries) { sess.save(e); } sess.flush(); sess.clear(); My 'logentry' class has no associations, the only interesting field is the id: @Entity @Table(name="log_entries") public class LogEntry { @Id @GeneratedValue public Long id; ..other fields - strings and ints... However, since it is oracle, i believe the @GeneratedValue will use the sequence generator. And i believe that only the 'identity' generator will stop bulk inserts. So if anyone can explain why it isn't running in batch mode, or how i can find out for sure if it is or isn't in batch mode, or find out why hibernate is silently dropping back to slow mode, i'd be most grateful. Thanks

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  • Issue with GCD and too many threads

    - by dariaa
    I have an image loader class which provided with NSURL loads and image from the web and executes completion block. Code is actually quite simple - (void)downloadImageWithURL:(NSString *)URLString completion:(BELoadImageCompletionBlock)completion { dispatch_async(_queue, ^{ // dispatch_async(dispatch_get_global_queue(DISPATCH_QUEUE_PRIORITY_HIGH, 0), ^{ UIImage *image = nil; NSURL *URL = [NSURL URLWithString:URLString]; if (URL) { image = [UIImage imageWithData:[NSData dataWithContentsOfURL:URL]]; } dispatch_async(dispatch_get_main_queue(), ^{ completion(image, URLString); }); }); } When I replace dispatch_async(_queue, ^{ with commented out dispatch_async(dispatch_get_global_queue(DISPATCH_QUEUE_PRIORITY_HIGH, 0), ^{ Images are loading much faster, wich is quite logical (before that images would be loaded one at a time, now a bunch of them are loading simultaneously). My issue is that I have perhaps 50 images and I call downloadImageWithURL:completion: method for all of them and when I use global queue instead of _queue my app eventually crashes and I see there are 85+ threads. Can the problem be that my calling dispatch_get_global_queue(DISPATCH_QUEUE_PRIORITY_HIGH, 0) 50 times in a row makes GCD create too many threads? I thought that gcd handles all the treading and makes sure the number of threads is not huge, but if it's not the case is there any way I can influence number of threads?

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  • Fast path cache generation for a connected node graph

    - by Sukasa
    I'm trying to get a faster pathfinding mechanism in place in a game I'm working on for a connected node graph. The nodes are classed into two types, "Networks" and "Routers." In this picture, the blue circles represent routers and the grey rectangles networks. Each network keeps a list of which routers it is connected to, and vice-versa. Routers cannot connect directly to other routers, and networks cannot connect directly to other networks. Networks list which routers they're connected to Routers do the same I need to get an algorithm that will map out a path, measured in the number of networks crossed, for each possible source and destination network excluding paths where the source and destination are the same network. I have one right now, however it is unusably slow, taking about two seconds to map the paths, which becomes incredibly noticeable for all connected players. The current algorithm is a depth-first brute-force search (It was thrown together in about an hour to just get the path caching working) which returns an array of networks in the order they are traversed, which explains why it's so slow. Are there any algorithms that are more efficient? As a side note, while these example graphs have four networks, the in-practice graphs have 55 networks and about 20 routers in use. Paths which are not possible also can occur, and as well at any time the network/router graph topography can change, requiring the path cache to be rebuilt. What approach/algorithm would likely provide the best results for this type of a graph?

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  • Approach for caching data from data logger

    - by filip-fku
    Greetings, I've been working on a C#.NET app that interacts with a data logger. The user can query and obtain logs for a specified time period, and view plots of the data. Typically a new data log is created every minute and stores a measurement for a few parameters. To get meaningful information out of the logger, a reasonable number of logs need to be acquired - data for at least a few days. The hardware interface is a UART to USB module on the device, which restricts transfers to a maximum of about 30 logs/second. This becomes quite slow when reading in the data acquired over a number of days/weeks. What I would like to do is improve the perceived performance for the user. I realize that with the hardware speed limitation the user will have to wait for the full download cycle at least the first time they acquire a larger set of data. My goal is to cache all data seen by the app, so that it can be obtained faster if ever requested again. The approach I have been considering is to use a light database, like SqlServerCe, that can store the data logs as they are received. I am then hoping to first search the cache prior to querying a device for logs. The cache would be updated with any logs obtained by the request that were not already cached. Finally my question - would you consider this to be a good approach? Are there any better alternatives you can think of? I've tried to search SO and Google for reinforcement of the idea, but I mostly run into discussions of web request/content caching. Thanks for any feedback!

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  • What is the fastest way to check if files are identical?

    - by ojblass
    If you have 1,000,0000 source files, you suspect they are all the same, and you want to compare them what is the current fasted method to compare those files? Assume they are Java files and platform where the comparison is done is not important. cksum is making me cry. When I mean identical I mean ALL identical. Update: I know about generating checksums. diff is laughable ... I want speed. Update: Don't get stuck on the fact they are source files. Pretend for example you took a million runs of a program with very regulated output. You want to prove all 1,000,000 versions of the output are the same. Update: read the number of blocks rather than bytes? Immediatly throw out those? Is that faster than finding the number of bytes? Update: Is this ANY different than the fastest way to compare two files?

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  • Why does this log output show the same answer in each iteration?

    - by Will Hancock
    OK, I was reading an article on optimising JS for Googles V8 engine, when i saw this code example... I nearly skimmed over it, but then I saw this; |=; a[0] |= b; a = new Array(); a[0] = 0; for (var b = 0; b < 10; b++) { console.log(a, b) a[0] |= b; // Much better! 2x faster. } a[0] |= b; So I ran it, in my console, with a console.log in the loop and resulted in 15; [15] 0 [15] 1 [15] 2 [15] 3 [15] 4 [15] 5 [15] 6 [15] 7 [15] 8 [15] 9 WHAT?!?! Where the hell does it get 15 from, on every iteration?!?!?! I've been a web dev for 7 years, and this has stumped me and a fellow colleague. Can somebody talk me through this code? Cheers.

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  • Move SELECT to SQL Server side

    - by noober
    Hello all, I have an SQLCLR trigger. It contains a large and messy SELECT inside, with parts like: (CASE WHEN EXISTS(SELECT * FROM INSERTED I WHERE I.ID = R.ID) THEN '1' ELSE '0' END) AS IsUpdated -- Is selected row just added? as well as JOINs etc. I like to have the result as a single table with all included. Question 1. Can I move this SELECT to SQL Server side? If yes, how to do this? Saying "move", I mean to create a stored procedure or something else that can be executed before reading dataset in while cycle. The 2 following questions make sense only if answer is "yes". Why do I want to move SELECT? First off, I don't like mixing SQL with C# code. At second, I suppose that server-side queries run faster, since the server have more chances to cache them. Question 2. Am I right? Is it some sort of optimizing? Also, the SELECT contains constant strings, but they are localizable. For instance, WHERE R.Status = "Enabled" "Enabled" should be changed for French, German etc. So, I want to write 2 static methods -- OnCreate and OnDestroy -- then mark them as stored procedures. When registering/unregistering my assembly on server side, just call them respectively. In OnCreate format the SELECT string, replacing {0}, {1}... with required values from the assembly resources. Then I can localize resources only, not every script. Question 3. Is it good idea? Is there an existing attribute to mark methods to be executed by SQL Server automatically after (un)registartion an assembly? Regards,

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  • How expensive is a context switch? Is it better to implement a manual task switch than to rely on OS

    - by Vilx-
    The title says it all. Imagine I have two (three, four, whatever) tasks that have to run in parallel. Now, the easy way to do this would be to create separate threads and forget about it. But on a plain old single-core CPU that would mean a lot of context switching - and we all know that context switching is big, bad, slow, and generally simply Evil. It should be avoided, right? On that note, if I'm writing the software from ground up anyway, I could go the extra mile and implement my own task-switching. Split each task in parts, save the state inbetween, and then switch among them within a single thread. Or, if I detect that there are multiple CPU cores, I could just give each task to a separate thread and all would be well. The second solution does have the advantage of adapting to the number of available CPU cores, but will the manual task-switch really be faster than the one in the OS core? Especially if I'm trying to make the whole thing generic with a TaskManager and an ITask, etc?

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  • optimize output value using a class and public member

    - by wiso
    Suppose you have a function, and you call it a lot of times, every time the function return a big object. I've optimized the problem using a functor that return void, and store the returning value in a public member: #include <vector> const int N = 100; std::vector<double> fun(const std::vector<double> & v, const int n) { std::vector<double> output = v; output[n] *= output[n]; return output; } class F { public: F() : output(N) {}; std::vector<double> output; void operator()(const std::vector<double> & v, const int n) { output = v; output[n] *= n; } }; int main() { std::vector<double> start(N,10.); std::vector<double> end(N); double a; // first solution for (unsigned long int i = 0; i != 10000000; ++i) a = fun(start, 2)[3]; // second solution F f; for (unsigned long int i = 0; i != 10000000; ++i) { f(start, 2); a = f.output[3]; } } Yes, I can use inline or optimize in an other way this problem, but here I want to stress on this problem: with the functor I declare and construct the output variable output only one time, using the function I do that every time it is called. The second solution is two time faster than the first with g++ -O1 or g++ -O2. What do you think about it, is it an ugly optimization?

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