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  • Optimizing python link matching regular expression

    - by Matt
    I have a regular expression, links = re.compile('<a(.+?)href=(?:"|\')?((?:https?://|/)[^\'"]+)(?:"|\')?(.*?)>(.+?)</a>',re.I).findall(data) to find links in some html, it is taking a long time on certain html, any optimization advice? One that it chokes on is http://freeyourmindonline.net/Blog/

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  • Linq Queries converting to lambda expressions ?

    - by Freshblood
    Hello from item in range where item % 2 ==0 select i ; is converting to lamda expressions as below range.where(item % 2 ==0).select(x=>x). I feel that first way of linq is translating next one and if it is ,so is there any optimization like this range.where(item & 2 == 0) instead of other one ?

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  • How do "modern JVMs" differ from older JVMs?

    - by Lord Torgamus
    Here's a phrase that I heard a lot throughout high school and university computer science classes: "That's not an issue for modern JVMs." Usually this would come up in discussions about overall performance or optimization strategies. It was always treated as a kind of magical final answer, though, as if it makes issues no longer worth thinking about. And that just leads me to wonder: what are the differences between the prototypical "modern JVM" and older JVMs, really?

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  • Improve long mysql query

    - by John Adawan
    I have a php mysql query like this $query = "SELECT * FROM articles FORCE INDEX (articleindex) WHERE category='$thiscat' and did>'$thisdid' and mid!='$thismid' and status='1' and group='$thisgroup' and pid>'$thispid' LIMIT 10"; As optimization, I've indexed all the parameters in articleindex and I use force index to force mysql to use the index, supposedly for faster processing. But it seems that this query is still quite slow and it's causing a jam and maxing out the max mysql connection limit. Let's discuss how we can improve on such long query.

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  • Improve long mysql query

    - by John Adawan
    I have a php mysql query like this $query = "SELECT * FROM articles FORCE INDEX (articleindex) WHERE category='$thiscat' and did>'$thisdid' and mid!='$thismid' and status='1' and group='$thisgroup' and pid>'$thispid' LIMIT 10"; As optimization, I've indexed all the parameters in articleindex and I use force index to force mysql to use the index, supposedly for faster processing. But it seems that this query is still quite slow and it's causing a jam and maxing out the max mysql connection limit. Let's discuss how we can improve on such long query.

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  • Ray-triangle intersetion

    - by gamemaker
    Hello! How can I test intersesion ray and triangle, and if it exist how to get distance from ray origin to intersection point?? What optimization I can use, if in my program I've got to check 1 ray to ~10000 triangles ??

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  • C: performance of assignments, binary operations, et cetera...

    - by Shinka
    I've heard many things about performance in C; casting is slow compared to normal assignments, functional call is slow, binary operation are much faster than normal operations, et cetera... I'm sure some of those things are specific to the architecture, and compiler optimization might make a huge difference, but I would like to see a chart to get a general idea what I should do and what I should avoid to write high-performance programs. Is there such a chart (or a website, a book, anything) ?

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  • Does acos, atan functions in stl uses lots of cpu cycles

    - by jan
    Hi all, I wanted to calculate the angle between two vectors but I have seen these inverse trig operations such as acos and atan uses lots of cpu cycles. Is there a way where I can get this calculation done without using these functions? Also, does these really hit you when you in your optimization?

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  • How I can Optimize this mySQL transaction within java code?

    - by worldpython
    Dear All, I am new to MySql database. I've large table(ID,...). I select ID frequently with java code and.And that make a heavy load on transaction select from tableName where ID=someID notes: 1.Database could be 100,000 records 2.I can't cache result 3.ID is a primary key 4.I try to optimize time needed to return result from query. Any ideas for optimization ? thanks in advance

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  • faster strlen ?

    - by Jack
    Typical strlen() traverse from first character till it finds \0. This requires you to traverse each and every character. In algorithm sense, its O(N). Is there any faster way to do this where input is vaguely defined. Like: length would be less than 50, or length would be around 200 characters. I thought of lookup blocks and all but didn't get any optimization.

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  • Does Microsoft make available the .obj files for its CRT versions to enable whole program optimizati

    - by Leeks and Leaks
    Given the potential performance improvements from LTCG (link time code generation, or whole program optimization), which requires the availability of .obj files, does Microsoft make available the .obj files for the various flavors of its MSVCRT releases? One would think this would be a good place for some potential gain. Not sure what they have to lose since the IL that is generated in the .obj files is not documented and processor specific.

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  • Database: Pipelined Functions

    - by Rachel
    I am new to the concept of Pipeline Functions. I have some questions regarding From Database point of view: What actually is Pipeline function ? What is the advantage of using Pipeline Function ? What challenges are solved using Pipeline Function ? Are the any optimization advantages of using Pipeline Function ? Thanks.

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  • C++[MSVC2010]: How does switch compile and how optimized and fast is it?

    - by ekul
    As I found out that I can use only numerical values in C++'s switch statements, I thought that there then must be some deeper difference between it and a bunch of if-else's. Therefore I asked myself: (How) does switch differ from if-elseif-elseif in terms of runtime speed, compile time optimization and general compilation? I'm mainly speaking of MSVC here.

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  • JVM memory management & garbage collection book?

    - by Max
    Hi. Could anyone advice a book (or any other source) that would thoroughly reveal internals of JVM memory management & garbage collection (optimization, work, circular references, pecularities, discussions for various JVM impls...)? [What I've found so far are separate articles devoted to various aspects but no weighty tome :). Some good materials for Hotspot implementation are here. ] Thanks a lot for any advice you give.

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  • About the armlink behavior when the linked object is not explicitly used by the main executable

    - by thincal
    I want to link the example with liba.so, and also the example is NOT using anything inside the liba.so ... armlink --userlibpath /mylib/lib liba.so --fpic --shared -o example main.o demo.o So finally I got nothing from: readelf -d example | grep NEEDED, it seems that armlink do some optimization to remove the linked library which is not really used by the "example" ? If I want to let the liba.so be always linked into example, what need I do with armlink options ? Any information is very appreciated ;)

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  • How to make a stack stable? Need help for an explicit resting contact scheme (2-dimensional)

    - by Register Sole
    Previously, I struggle with the sequential impulse-based method I developed. Thanks to jedediah referring me to this paper, I managed to rebuild the codes and implement the simultaneous impulse based method with Projected-Gauss-Seidel (PGS) iterative solver as described by Erin Catto (mentioned in the reference of the paper as [Catt05]). So here's how it currently is: The simulation handles 2-dimensional rotating convex polygons. Detection is using separating-axis test, with a SKIN, meaning closest points between two polygons is detected and determined if their distance is less than SKIN. To resolve collision, simultaneous impulse-based method is used. It is solved using iterative solver (PGS-solver) as in Erin Catto's paper. Error-correction is implemented using Baumgarte's stabilization (you can refer to either paper for this) using J V = beta/dt*overlap, J is the Jacobian for the constraints, V the matrix containing the velocities of the bodies, beta an error-correction parameter that is better be < 1, dt the time-step taken by the engine, and overlap, the overlap between the bodies (true overlap, so SKIN is ignored). However, it is still less stable than I expected :s I tried to stack hexagons (or squares, doesn't really matter), and even with only 4 to 5 of them, they would swing! Also note that I am not looking for a sleeping scheme. But I would settle if you have any explicit scheme to handle resting contacts. That said, I would be more than happy if you have a way of treating it generally (as continuous collision, instead of explicitly as a special state). Ideas I have tried: Using simultaneous position based error correction as described in the paper in section 5.3.2, turned out to be worse than the current scheme. If you want to know the parameters I used: Hexagons, side 50 (pixels) gravity 2400 (pixels/sec^2) time-step 1/60 (sec) beta 0.1 restitution 0 to 0.2 coeff. of friction 0.2 PGS iteration 10 initial separation 10 (pixels) mass 1 (unit is irrelevant for now, i modified velocity directly<-impulse method) inertia 1/1000 Thanks in advance! I really appreciate any help from you guys!! :) EDIT In response to Cholesky's comment about warm starting the solver and Baumgarte: Oh right, I forgot to mention! I do save the contact history and the impulse determined in this time step to be used as initial guess in the next time step. As for the Baumgarte, here's what actually happens in the code. Collision is detected when the bodies' closest distance is less than SKIN, meaning they are actually still separated. If at this moment, I used the PGS solver without Baumgarte, restitution of 0 alone would be able to stop the bodies, separated by a distance of ~SKIN, in mid-air! So this isn't right, I want to have the bodies touching each other. So I turn on the Baumgarte, where its role is actually to pull the bodies together! Weird I know, a scheme intended to push the body apart becomes useful for the reverse. Also, I found that if I increase the number of iteration to 100, stacks become much more stable, though the program becomes so slow. UPDATE Since the stack swings left and right, could it be something is wrong with my friction model? Current friction constraint: relative_tangential_velocity = 0

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  • Does this prove a network bandwidth bottleneck?

    - by Yuji Tomita
    I've incorrectly assumed that my internal AB testing means my server can handle 1k concurrency @3k hits per second. My theory at at the moment is that the network is the bottleneck. The server can't send enough data fast enough. External testing from blitz.io at 1k concurrency shows my hits/s capping off at 180, with pages taking longer and longer to respond as the server is only able to return 180 per second. I've served a blank file from nginx and benched it: it scales 1:1 with concurrency. Now to rule out IO / memcached bottlenecks (nginx normally pulls from memcached), I serve up a static version of the cached page from the filesystem. The results are very similar to my original test; I'm capped at around 180 RPS. Splitting the HTML page in half gives me double the RPS, so it's definitely limited by the size of the page. If I internally ApacheBench from the local server, I get consistent results of around 4k RPS on both the Full Page and the Half Page, at high transfer rates. Transfer rate: 62586.14 [Kbytes/sec] received If I AB from an external server, I get around 180RPS - same as the blitz.io results. How do I know it's not intentional throttling? If I benchmark from multiple external servers, all results become poor which leads me to believe the problem is in MY servers outbound traffic, not a download speed issue with my benchmarking servers / blitz.io. So I'm back to my conclusion that my server can't send data fast enough. Am I right? Are there other ways to interpret this data? Is the solution/optimization to set up multiple servers + load balancing that can each serve 180 hits per second? I'm quite new to server optimization, so I'd appreciate any confirmation interpreting this data. Outbound traffic Here's more information about the outbound bandwidth: The network graph shows a maximum output of 16 Mb/s: 16 megabits per second. Doesn't sound like much at all. Due to a suggestion about throttling, I looked into this and found that linode has a 50mbps cap (which I'm not even close to hitting, apparently). I had it raised to 100mbps. Since linode caps my traffic, and I'm not even hitting it, does this mean that my server should indeed be capable of outputting up to 100mbps but is limited by some other internal bottleneck? I just don't understand how networks at this large of a scale work; can they literally send data as fast as they can read from the HDD? Is the network pipe that big? In conclusion 1: Based on the above, I'm thinking I can definitely raise my 180RPS by adding an nginx load balancer on top of a multi nginx server setup at exactly 180RPS per server behind the LB. 2: If linode has a 50/100mbit limit that I'm not hitting at all, there must be something I can do to hit that limit with my single server setup. If I can read / transmit data fast enough locally, and linode even bothers to have a 50mbit/100mbit cap, there must be an internal bottleneck that's not allowing me to hit those caps that I'm not sure how to detect. Correct? I realize the question is huge and vague now, but I'm not sure how to condense it. Any input is appreciated on any conclusion I've made.

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  • Worse is better. Is there an example?

    - by J.F. Sebastian
    Is there a widely-used algorithm that has time complexity worse than that of another known algorithm but it is a better choice in all practical situations (worse complexity but better otherwise)? An acceptable answer might be in a form: There are algorithms A and B that have O(N**2) and O(N) time complexity correspondingly, but B has such a big constant that it has no advantages over A for inputs less then a number of atoms in the Universe. Examples highlights from the answers: Simplex algorithm -- worst-case is exponential time -- vs. known polynomial-time algorithms for convex optimization problems. A naive median of medians algorithm -- worst-case O(N**2) vs. known O(N) algorithm. Backtracking regex engines -- worst-case exponential vs. O(N) Thompson NFA -based engines. All these examples exploit worst-case vs. average scenarios. Are there examples that do not rely on the difference between the worst case vs. average case scenario? Related: The Rise of ``Worse is Better''. (For the purpose of this question the "Worse is Better" phrase is used in a narrower (namely -- algorithmic time-complexity) sense than in the article) Python's Design Philosophy: The ABC group strived for perfection. For example, they used tree-based data structure algorithms that were proven to be optimal for asymptotically large collections (but were not so great for small collections). This example would be the answer if there were no computers capable of storing these large collections (in other words large is not large enough in this case). Coppersmith–Winograd algorithm for square matrix multiplication is a good example (it is the fastest (2008) but it is inferior to worse algorithms). Any others? From the wikipedia article: "It is not used in practice because it only provides an advantage for matrices so large that they cannot be processed by modern hardware (Robinson 2005)."

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