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  • gcc memory alignment pragma

    - by aaa
    hello. Does gcc have memory alignment pragma, akin #pragma vector aligned in Intel compiler? I would like to tell compiler to optimize particular loop using aligned loads/store instructions. Thanks

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  • Does Delphi really handle dynamic classes better than static?

    - by John
    Hello, I was told more than once that Delphi handles dynamic classes better than static.Thereby using the following: type Tsomeclass=class(TObject) private procedure proc1; public someint:integer; procedure proc2; end; var someclass:TSomeclass; implementation ... initialization someclass:=TSomeclass.Create; finalization someclass.Free; rather than type Tsomeclass=class private class procedure proc1; public var someint:integer; class procedure proc2; end; 90% of the classes in the project I'm working on have and need only one instance.Do I really have to use the first way for using those classes? Is it better optimized,handled by Delphi? Sorry,I have no arguments to backup this hypothesis,but I want an expert's opinion. Thanks in advance!

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  • SQL Table Setup Advice

    - by Ozzy
    Hi all. Basically I have an xml feed from an offsite server. The xml feed has one parameter ?value=n now N can only be between 1 and 30 What ever value i pick, there will always be 4000 rows returned from the XML file. My script will call this xml file 30 times for each value once a day. So thats 120000 rows. I will be doing quite complicated queries on these rows. But the main thing is I will always filter by value first so SELECT * WHERE value = 'N' etc. That will ALWAYS be used. Now is it better to have one table where all 120k rows are stored? or 30 tables were 4k rows are stored? EDIT: the SQL database in question will be MySQL

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  • How does loop address alignment affect the speed on Intel x86_64?

    - by Alexander Gololobov
    I'm seeing 15% performance degradation of the same C++ code compiled to exactly same machine instructions but located on differently aligned addresses. When my tiny main loop starts at 0x415220 it's faster then when it is at 0x415250. I'm running this on Intel Core2 Duo. I use gcc 4.4.5 on x86_64 Ubuntu. Can anybody explain the cause of slowdown and how I can force gcc to optimally align the loop? Here is the disassembly for both cases with profiler annotation: 415220 576 12.56% |XXXXXXXXXXXXXX 48 c1 eb 08 shr $0x8,%rbx 415224 110 2.40% |XX 0f b6 c3 movzbl %bl,%eax 415227 0.00% | 41 0f b6 04 00 movzbl (%r8,%rax,1),%eax 41522c 40 0.87% | 48 8b 04 c1 mov (%rcx,%rax,8),%rax 415230 806 17.58% |XXXXXXXXXXXXXXXXXXX 4c 63 f8 movslq %eax,%r15 415233 186 4.06% |XXXX 48 c1 e8 20 shr $0x20,%rax 415237 102 2.22% |XX 4c 01 f9 add %r15,%rcx 41523a 414 9.03% |XXXXXXXXXX a8 0f test $0xf,%al 41523c 680 14.83% |XXXXXXXXXXXXXXXX 74 45 je 415283 ::Run(char const*, char const*)+0x4b3 41523e 0.00% | 41 89 c7 mov %eax,%r15d 415241 0.00% | 41 83 e7 01 and $0x1,%r15d 415245 0.00% | 41 83 ff 01 cmp $0x1,%r15d 415249 0.00% | 41 89 c7 mov %eax,%r15d 415250 679 13.05% |XXXXXXXXXXXXXXXX 48 c1 eb 08 shr $0x8,%rbx 415254 124 2.38% |XX 0f b6 c3 movzbl %bl,%eax 415257 0.00% | 41 0f b6 04 00 movzbl (%r8,%rax,1),%eax 41525c 43 0.83% |X 48 8b 04 c1 mov (%rcx,%rax,8),%rax 415260 828 15.91% |XXXXXXXXXXXXXXXXXXX 4c 63 f8 movslq %eax,%r15 415263 388 7.46% |XXXXXXXXX 48 c1 e8 20 shr $0x20,%rax 415267 141 2.71% |XXX 4c 01 f9 add %r15,%rcx 41526a 634 12.18% |XXXXXXXXXXXXXXX a8 0f test $0xf,%al 41526c 749 14.39% |XXXXXXXXXXXXXXXXXX 74 45 je 4152b3 ::Run(char const*, char const*)+0x4c3 41526e 0.00% | 41 89 c7 mov %eax,%r15d 415271 0.00% | 41 83 e7 01 and $0x1,%r15d 415275 0.00% | 41 83 ff 01 cmp $0x1,%r15d 415279 0.00% | 41 89 c7 mov %eax,%r15d

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  • PostgreSQL - fetch the row which has the Max value for a column

    - by Joshua Berry
    I'm dealing with a Postgres table (called "lives") that contains records with columns for time_stamp, usr_id, transaction_id, and lives_remaining. I need a query that will give me the most recent lives_remaining total for each usr_id There are multiple users (distinct usr_id's) time_stamp is not a unique identifier: sometimes user events (one by row in the table) will occur with the same time_stamp. trans_id is unique only for very small time ranges: over time it repeats remaining_lives (for a given user) can both increase and decrease over time example: time_stamp|lives_remaining|usr_id|trans_id ----------------------------------------- 07:00 | 1 | 1 | 1 09:00 | 4 | 2 | 2 10:00 | 2 | 3 | 3 10:00 | 1 | 2 | 4 11:00 | 4 | 1 | 5 11:00 | 3 | 1 | 6 13:00 | 3 | 3 | 1 As I will need to access other columns of the row with the latest data for each given usr_id, I need a query that gives a result like this: time_stamp|lives_remaining|usr_id|trans_id ----------------------------------------- 11:00 | 3 | 1 | 6 10:00 | 1 | 2 | 4 13:00 | 3 | 3 | 1 As mentioned, each usr_id can gain or lose lives, and sometimes these timestamped events occur so close together that they have the same timestamp! Therefore this query won't work: SELECT b.time_stamp,b.lives_remaining,b.usr_id,b.trans_id FROM (SELECT usr_id, max(time_stamp) AS max_timestamp FROM lives GROUP BY usr_id ORDER BY usr_id) a JOIN lives b ON a.max_timestamp = b.time_stamp Instead, I need to use both time_stamp (first) and trans_id (second) to identify the correct row. I also then need to pass that information from the subquery to the main query that will provide the data for the other columns of the appropriate rows. This is the hacked up query that I've gotten to work: SELECT b.time_stamp,b.lives_remaining,b.usr_id,b.trans_id FROM (SELECT usr_id, max(time_stamp || '*' || trans_id) AS max_timestamp_transid FROM lives GROUP BY usr_id ORDER BY usr_id) a JOIN lives b ON a.max_timestamp_transid = b.time_stamp || '*' || b.trans_id ORDER BY b.usr_id Okay, so this works, but I don't like it. It requires a query within a query, a self join, and it seems to me that it could be much simpler by grabbing the row that MAX found to have the largest timestamp and trans_id. The table "lives" has tens of millions of rows to parse, so I'd like this query to be as fast and efficient as possible. I'm new to RDBM and Postgres in particular, so I know that I need to make effective use of the proper indexes. I'm a bit lost on how to optimize. I found a similar discussion here. Can I perform some type of Postgres equivalent to an Oracle analytic function? Any advice on accessing related column information used by an aggregate function (like MAX), creating indexes, and creating better queries would be much appreciated! P.S. You can use the following to create my example case: create TABLE lives (time_stamp timestamp, lives_remaining integer, usr_id integer, trans_id integer); insert into lives values ('2000-01-01 07:00', 1, 1, 1); insert into lives values ('2000-01-01 09:00', 4, 2, 2); insert into lives values ('2000-01-01 10:00', 2, 3, 3); insert into lives values ('2000-01-01 10:00', 1, 2, 4); insert into lives values ('2000-01-01 11:00', 4, 1, 5); insert into lives values ('2000-01-01 11:00', 3, 1, 6); insert into lives values ('2000-01-01 13:00', 3, 3, 1);

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  • What is the best algorithm for this array-comparison problem?

    - by mark
    What is the most efficient for speed algorithm to solve the following problem? Given 6 arrays, D1,D2,D3,D4,D5 and D6 each containing 6 numbers like: D1[0] = number D2[0] = number ...... D6[0] = number D1[1] = another number D2[1] = another number .... ..... .... ...... .... D1[5] = yet another number .... ...... .... Given a second array ST1, containing 1 number: ST1[0] = 6 Given a third array ans, containing 6 numbers: ans[0] = 3, ans[1] = 4, ans[2] = 5, ......ans[5] = 8 Using as index for the arrays D1,D2,D3,D4,D5 and D6, the number that goes from 0, to the number stored in ST1[0] minus one, in this example 6, so from 0 to 6-1, compare each res array against each D array My algorithm so far is: I tried to keep everything unlooped as much as possible. EML := ST1[0] //number contained in ST1[0] EML1 := 0 //start index for the arrays D While EML1 < EML if D1[ELM1] = ans[0] goto two if D2[ELM1] = ans[0] goto two if D3[ELM1] = ans[0] goto two if D4[ELM1] = ans[0] goto two if D5[ELM1] = ans[0] goto two if D6[ELM1] = ans[0] goto two ELM1 = ELM1 + 1 return 0 //If the ans[0] number is not found in either D1[0-6], D2[0-6].... D6[0-6] return 0 which will then exclude ans[0-6] numbers two: EML1 := 0 start index for arrays Ds While EML1 < EML if D1[ELM1] = ans[1] goto three if D2[ELM1] = ans[1] goto three if D3[ELM1] = ans[1] goto three if D4[ELM1] = ans[1] goto three if D5[ELM1] = ans[1] goto three if D6[ELM1] = ans[1] goto three ELM1 = ELM1 + 1 return 0 //If the ans[1] number is not found in either D1[0-6], D2[0-6].... D6[0-6] return 0 which will then exclude ans[0-6] numbers three: EML1 := 0 start index for arrays Ds While EML1 < EML if D1[ELM1] = ans[2] goto four if D2[ELM1] = ans[2] goto four if D3[ELM1] = ans[2] goto four if D4[ELM1] = ans[2] goto four if D5[ELM1] = ans[2] goto four if D6[ELM1] = ans[2] goto four ELM1 = ELM1 + 1 return 0 //If the ans[2] number is not found in either D1[0-6], D2[0-6].... D6[0-6] return 0 which will then exclude ans[0-6] numbers four: EML1 := 0 start index for arrays Ds While EML1 < EML if D1[ELM1] = ans[3] goto five if D2[ELM1] = ans[3] goto five if D3[ELM1] = ans[3] goto five if D4[ELM1] = ans[3] goto five if D5[ELM1] = ans[3] goto five if D6[ELM1] = ans[3] goto five ELM1 = ELM1 + 1 return 0 //If the ans[3] number is not found in either D1[0-6], D2[0-6].... D6[0-6] return 0 which will then exclude ans[0-6] numbers five: EML1 := 0 start index for arrays Ds While EML1 < EML if D1[ELM1] = ans[4] goto six if D2[ELM1] = ans[4] goto six if D3[ELM1] = ans[4] goto six if D4[ELM1] = ans[4] goto six if D5[ELM1] = ans[4] goto six if D6[ELM1] = ans[4] goto six ELM1 = ELM1 + 1 return 0 //If the ans[4] number is not found in either D1[0-6], D2[0-6].... D6[0-6] return 0 which will then exclude ans[0-6] numbers six: EML1 := 0 start index for arrays Ds While EML1 < EML if D1[ELM1] = ans[5] return 1 ////If the ans[1] number is not found in either D1[0-6]..... if D2[ELM1] = ans[5] return 1 which will then include ans[0-6] numbers return 1 if D3[ELM1] = ans[5] return 1 if D4[ELM1] = ans[5] return 1 if D5[ELM1] = ans[5] return 1 if D6[ELM1] = ans[5] return 1 ELM1 = ELM1 + 1 return 0 As language of choice, it would be pure c

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  • Why doesn't gcc remove this check of a non-volatile variable?

    - by Thomas
    This question is mostly academic. I ask out of curiosity, not because this poses an actual problem for me. Consider the following incorrect C program. #include <signal.h> #include <stdio.h> static int running = 1; void handler(int u) { running = 0; } int main() { signal(SIGTERM, handler); while (running) ; printf("Bye!\n"); return 0; } This program is incorrect because the handler interrupts the program flow, so running can be modified at any time and should therefore be declared volatile. But let's say the programmer forgot that. gcc 4.3.3, with the -O3 flag, compiles the loop body (after one initial check of the running flag) down to the infinite loop .L7: jmp .L7 which was to be expected. Now we put something trivial inside the while loop, like: while (running) putchar('.'); And suddenly, gcc does not optimize the loop condition anymore! The loop body's assembly now looks like this (again at -O3): .L7: movq stdout(%rip), %rsi movl $46, %edi call _IO_putc movl running(%rip), %eax testl %eax, %eax jne .L7 We see that running is re-loaded from memory each time through the loop; it is not even cached in a register. Apparently gcc now thinks that the value of running could have changed. So why does gcc suddenly decide that it needs to re-check the value of running in this case?

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  • Jruby rspec to be run parallely

    - by Priyank
    Hi. Is there something like Spork for Jruby too? We want to parallelize our specs to run faster and pre-load the classes while running the rake task; however we have not been able to do so. Since our project is considerable in size, specs take about 15 minutes to complete and this poses a serious challenge to quick turnaround. Any ideas are more than welcome. Cheers

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  • Does the .NET CLR Really Optimize for the Current Processor

    - by dewald
    When I read about the performance of JITted languages like C# or Java, authors usually say that they should/could theoretically outperform many native-compiled applications. The theory being that native applications are usually just compiled for a processor family (like x86), so the compiler cannot make certain optimizations as they may not truly be optimizations on all processors. On the other hand, the CLR can make processor-specific optimizations during the JIT process. Does anyone know if Microsoft's (or Mono's) CLR actually performs processor-specific optimizations during the JIT process? If so, what kind of optimizations?

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  • Can anyone recommend a decent tool for optimizing images other than Photoshop

    - by toomanyairmiles
    Can anyone recommend a decent tool for optimising images other than adobe photoshop, the gimp etc? I'm looking to optimise images for the web preferably online and free. Basically I have a client who can't install additional software on their work PC but needs to optimise photographs and other images for their website and is presently uploading 1 or 2 Mb files. On a personal level I'm interested to see what other people are using...

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  • Any difference between lazy loading Javascript files vs. placing just before </body>

    - by mhr
    Looked around, couldn't find this specific question discussed. Pretty sure the difference is negligible, just curious as to your thoughts. Scenario: All Javascript that doesn't need to be loaded before page render has been placed just before the closing </body> tag. Are there any benefits or detriments to lazy loading these instead through some Javascript code in the head that executes when the DOM load/ready event is fired? Let's say that this only concerns downloading one entire .js file full of functions and not lazy loading several individual files as needed upon usage. Hope that's clear, thanks.

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  • help optimize sql query

    - by msony
    I have tracking table tbl_track with id, session_id, created_date fields I need count unique session_id for one day here what i got: select count(0) from ( select distinct session_id from tbl_track where created_date between getdate()-1 and getdate() group by session_id )tbl im feeling that it could be better solution for it

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  • One letter game problem?

    - by Alex K
    Recently at a job interview I was given the following problem: Write a script capable of running on the command line as python It should take in two words on the command line (or optionally if you'd prefer it can query the user to supply the two words via the console). Given those two words: a. Ensure they are of equal length b. Ensure they are both words present in the dictionary of valid words in the English language that you downloaded. If so compute whether you can reach the second word from the first by a series of steps as follows a. You can change one letter at a time b. Each time you change a letter the resulting word must also exist in the dictionary c. You cannot add or remove letters If the two words are reachable, the script should print out the path which leads as a single, shortest path from one word to the other. You can /usr/share/dict/words for your dictionary of words. My solution consisted of using breadth first search to find a shortest path between two words. But apparently that wasn't good enough to get the job :( Would you guys know what I could have done wrong? Thank you so much. import collections import functools import re def time_func(func): import time def wrapper(*args, **kwargs): start = time.time() res = func(*args, **kwargs) timed = time.time() - start setattr(wrapper, 'time_taken', timed) return res functools.update_wrapper(wrapper, func) return wrapper class OneLetterGame: def __init__(self, dict_path): self.dict_path = dict_path self.words = set() def run(self, start_word, end_word): '''Runs the one letter game with the given start and end words. ''' assert len(start_word) == len(end_word), \ 'Start word and end word must of the same length.' self.read_dict(len(start_word)) path = self.shortest_path(start_word, end_word) if not path: print 'There is no path between %s and %s (took %.2f sec.)' % ( start_word, end_word, find_shortest_path.time_taken) else: print 'The shortest path (found in %.2f sec.) is:\n=> %s' % ( self.shortest_path.time_taken, ' -- '.join(path)) def _bfs(self, start): '''Implementation of breadth first search as a generator. The portion of the graph to explore is given on demand using get_neighboors. Care was taken so that a vertex / node is explored only once. ''' queue = collections.deque([(None, start)]) inqueue = set([start]) while queue: parent, node = queue.popleft() yield parent, node new = set(self.get_neighbours(node)) - inqueue inqueue = inqueue | new queue.extend([(node, child) for child in new]) @time_func def shortest_path(self, start, end): '''Returns the shortest path from start to end using bfs. ''' assert start in self.words, 'Start word not in dictionnary.' assert end in self.words, 'End word not in dictionnary.' paths = {None: []} for parent, child in self._bfs(start): paths[child] = paths[parent] + [child] if child == end: return paths[child] return None def get_neighbours(self, word): '''Gets every word one letter away from the a given word. We do not keep these words in memory because bfs accesses a given vertex only once. ''' neighbours = [] p_word = ['^' + word[0:i] + '\w' + word[i+1:] + '$' for i, w in enumerate(word)] p_word = '|'.join(p_word) for w in self.words: if w != word and re.match(p_word, w, re.I|re.U): neighbours += [w] return neighbours def read_dict(self, size): '''Loads every word of a specific size from the dictionnary into memory. ''' for l in open(self.dict_path): l = l.decode('latin-1').strip().lower() if len(l) == size: self.words.add(l) if __name__ == '__main__': import sys if len(sys.argv) not in [3, 4]: print 'Usage: python one_letter_game.py start_word end_word' else: g = OneLetterGame(dict_path = '/usr/share/dict/words') try: g.run(*sys.argv[1:]) except AssertionError, e: print e

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  • efficacy of register allocation algorithms!

    - by aksci
    i'm trying to do a research/project on register allocation using graph coloring where i am to test the efficiency of different optimizing register allocation algorithms in different scenarios. how do i start? what are the prerequisites and the grounds with which i can test them. what all algos can i use? thank you!

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  • F# - Facebook Hacker Cup - Double Squares

    - by Jacob
    I'm working on strengthening my F#-fu and decided to tackle the Facebook Hacker Cup Double Squares problem. I'm having some problems with the run-time and was wondering if anyone could help me figure out why it is so much slower than my C# equivalent. There's a good description from another post; Source: Facebook Hacker Cup Qualification Round 2011 A double-square number is an integer X which can be expressed as the sum of two perfect squares. For example, 10 is a double-square because 10 = 3^2 + 1^2. Given X, how can we determine the number of ways in which it can be written as the sum of two squares? For example, 10 can only be written as 3^2 + 1^2 (we don't count 1^2 + 3^2 as being different). On the other hand, 25 can be written as 5^2 + 0^2 or as 4^2 + 3^2. You need to solve this problem for 0 = X = 2,147,483,647. Examples: 10 = 1 25 = 2 3 = 0 0 = 1 1 = 1 My basic strategy (which I'm open to critique on) is to; Create a dictionary (for memoize) of the input numbers initialzed to 0 Get the largest number (LN) and pass it to count/memo function Get the LN square root as int Calculate squares for all numbers 0 to LN and store in dict Sum squares for non repeat combinations of numbers from 0 to LN If sum is in memo dict, add 1 to memo Finally, output the counts of the original numbers. Here is the F# code (See code changes at bottom) I've written that I believe corresponds to this strategy (Runtime: ~8:10); open System open System.Collections.Generic open System.IO /// Get a sequence of values let rec range min max = seq { for num in [min .. max] do yield num } /// Get a sequence starting from 0 and going to max let rec zeroRange max = range 0 max /// Find the maximum number in a list with a starting accumulator (acc) let rec maxNum acc = function | [] -> acc | p::tail when p > acc -> maxNum p tail | p::tail -> maxNum acc tail /// A helper for finding max that sets the accumulator to 0 let rec findMax nums = maxNum 0 nums /// Build a collection of combinations; ie [1,2,3] = (1,1), (1,2), (1,3), (2,2), (2,3), (3,3) let rec combos range = seq { let count = ref 0 for inner in range do for outer in Seq.skip !count range do yield (inner, outer) count := !count + 1 } let rec squares nums = let dict = new Dictionary<int, int>() for s in nums do dict.[s] <- (s * s) dict /// Counts the number of possible double squares for a given number and keeps track of other counts that are provided in the memo dict. let rec countDoubleSquares (num: int) (memo: Dictionary<int, int>) = // The highest relevent square is the square root because it squared plus 0 squared is the top most possibility let maxSquare = System.Math.Sqrt((float)num) // Our relevant squares are 0 to the highest possible square; note the cast to int which shouldn't hurt. let relSquares = range 0 ((int)maxSquare) // calculate the squares up front; let calcSquares = squares relSquares // Build up our square combinations; ie [1,2,3] = (1,1), (1,2), (1,3), (2,2), (2,3), (3,3) for (sq1, sq2) in combos relSquares do let v = calcSquares.[sq1] + calcSquares.[sq2] // Memoize our relevant results if memo.ContainsKey(v) then memo.[v] <- memo.[v] + 1 // return our count for the num passed in memo.[num] // Read our numbers from file. //let lines = File.ReadAllLines("test2.txt") //let nums = [ for line in Seq.skip 1 lines -> Int32.Parse(line) ] // Optionally, read them from straight array let nums = [1740798996; 1257431873; 2147483643; 602519112; 858320077; 1048039120; 415485223; 874566596; 1022907856; 65; 421330820; 1041493518; 5; 1328649093; 1941554117; 4225; 2082925; 0; 1; 3] // Initialize our memoize dictionary let memo = new Dictionary<int, int>() for num in nums do memo.[num] <- 0 // Get the largest number in our set, all other numbers will be memoized along the way let maxN = findMax nums // Do the memoize let maxCount = countDoubleSquares maxN memo // Output our results. for num in nums do printfn "%i" memo.[num] // Have a little pause for when we debug let line = Console.Read() And here is my version in C# (Runtime: ~1:40: using System; using System.Collections.Generic; using System.Diagnostics; using System.IO; using System.Linq; using System.Text; namespace FBHack_DoubleSquares { public class TestInput { public int NumCases { get; set; } public List<int> Nums { get; set; } public TestInput() { Nums = new List<int>(); } public int MaxNum() { return Nums.Max(); } } class Program { static void Main(string[] args) { // Read input from file. //TestInput input = ReadTestInput("live.txt"); // As example, load straight. TestInput input = new TestInput { NumCases = 20, Nums = new List<int> { 1740798996, 1257431873, 2147483643, 602519112, 858320077, 1048039120, 415485223, 874566596, 1022907856, 65, 421330820, 1041493518, 5, 1328649093, 1941554117, 4225, 2082925, 0, 1, 3, } }; var maxNum = input.MaxNum(); Dictionary<int, int> memo = new Dictionary<int, int>(); foreach (var num in input.Nums) { if (!memo.ContainsKey(num)) memo.Add(num, 0); } DoMemoize(maxNum, memo); StringBuilder sb = new StringBuilder(); foreach (var num in input.Nums) { //Console.WriteLine(memo[num]); sb.AppendLine(memo[num].ToString()); } Console.Write(sb.ToString()); var blah = Console.Read(); //File.WriteAllText("out.txt", sb.ToString()); } private static int DoMemoize(int num, Dictionary<int, int> memo) { var highSquare = (int)Math.Floor(Math.Sqrt(num)); var squares = CreateSquareLookup(highSquare); var relSquares = squares.Keys.ToList(); Debug.WriteLine("Starting - " + num.ToString()); Debug.WriteLine("RelSquares.Count = {0}", relSquares.Count); int sum = 0; var index = 0; foreach (var square in relSquares) { foreach (var inner in relSquares.Skip(index)) { sum = squares[square] + squares[inner]; if (memo.ContainsKey(sum)) memo[sum]++; } index++; } if (memo.ContainsKey(num)) return memo[num]; return 0; } private static TestInput ReadTestInput(string fileName) { var lines = File.ReadAllLines(fileName); var input = new TestInput(); input.NumCases = int.Parse(lines[0]); foreach (var lin in lines.Skip(1)) { input.Nums.Add(int.Parse(lin)); } return input; } public static Dictionary<int, int> CreateSquareLookup(int maxNum) { var dict = new Dictionary<int, int>(); int square; foreach (var num in Enumerable.Range(0, maxNum)) { square = num * num; dict[num] = square; } return dict; } } } Thanks for taking a look. UPDATE Changing the combos function slightly will result in a pretty big performance boost (from 8 min to 3:45): /// Old and Busted... let rec combosOld range = seq { let rangeCache = Seq.cache range let count = ref 0 for inner in rangeCache do for outer in Seq.skip !count rangeCache do yield (inner, outer) count := !count + 1 } /// The New Hotness... let rec combos maxNum = seq { for i in 0..maxNum do for j in i..maxNum do yield i,j }

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  • speed up wamp server + drupal on windows vista

    - by Andrew Welch
    Hi, My localhost performance with drupal six is pretty slow. I found a solution to add a # before the :: localhost line of the system32/etc/hosts file but this was something I had already done and didn't help much. does anyone know of any other optimisations that might work? tHanks Andy

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  • 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)); }

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  • Try to fill the GAE datastore but the code consumes to much cpu time. How to optimize this?

    - by Neverland
    I try to get the list of images in Amazon EC2 inside the Google datastore. I want to realize this with a cron job inside the GAE. class AmazonEC2uswest(db.Model): ami = db.StringProperty(required=True) mani = db.StringProperty() typ = db.StringProperty() arch = db.StringProperty() state = db.StringProperty() owner = db.StringProperty() class CronAMIsAmazonUS_WEST(webapp.RequestHandler): def get(self): aws_access_key_id_admin = "<secret>" aws_secret_access_key_admin = "<secret>" conn_us_west = boto.ec2.connect_to_region('us-west-1', aws_access_key_id=aws_access_key_id_admin, aws_secret_access_key=aws_secret_access_key_admin, is_secure = False) liste_images_us_west = conn_us_west.get_all_images() laenge_liste_images_us_west = len(liste_images_us_west) for i in range(laenge_liste_images_us_west): datastore_uswest_AMIs = AmazonEC2uswest(ami=liste_images_us_west[i].id, mani=str(liste_images_us_west[i].location), typ=liste_images_us_west[i].type, arch=liste_images_us_west[i].architecture, state=liste_images_us_west[i].state, owner=liste_images_us_west[i].ownerId) datastore_uswest_AMIs.put() The problem: Getting the list with get_all_images() lasts only a few seconds. But writing the data to the Google datastore needs way too much CPU time. My IBM T42p (P4M with 2GHz) needs for that piece of code approx. 1 Minute! Is it possible to optimize my code in a way that it needs fewer CPU time?

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  • Good Starting Points for Optimizing Database Calls in Ruby on Rails?

    - by viatropos
    I have a menu in Rails which grabs a nested tree of Post models, each which have a Slug model associated via a polymorphic association (using the friendly_id gem for slugs and awesome_nested_set for the tree). The database output in development looks like this (here's the full gist): SQL (0.4ms) SELECT COUNT(*) AS count_id FROM "posts" WHERE ("posts".parent_id = 39) CACHE (0.0ms) SELECT "posts".* FROM "posts" WHERE ("posts"."id" = 13) LIMIT 1 CACHE (0.0ms) SELECT "slugs".* FROM "slugs" WHERE ("slugs".sluggable_id = 13 AND "slugs".sluggable_type = 'Post') ORDER BY id DESC LIMIT 1 Slug Load (0.4ms) SELECT "slugs".* FROM "slugs" WHERE ("slugs".sluggable_id = 40 AND "slugs".sluggable_type = 'Post') ORDER BY id DESC LIMIT 1 SQL (0.3ms) SELECT COUNT(*) AS count_id FROM "posts" WHERE ("posts".parent_id = 40) CACHE (0.0ms) SELECT "posts".* FROM "posts" WHERE ("posts"."id" = 13) LIMIT 1 CACHE (0.0ms) SELECT "slugs".* FROM "slugs" WHERE ("slugs".sluggable_id = 13 AND "slugs".sluggable_type = 'Post') ORDER BY id DESC LIMIT 1 Slug Load (0.4ms) SELECT "slugs".* FROM "slugs" WHERE ("slugs".sluggable_id = 41 AND "slugs".sluggable_type = 'Post') ORDER BY id DESC LIMIT 1 ... Rendered shared/_menu.html.haml (907.6ms) What are some quick things I should always do to optimize this from the start (easy things)? Some things I'm thinking now are: Can Rails 3 eager load the whole Post tree + associated Slugs in one DB call? Can I do that easily with named scopes or custom SQL? What is best practice in this situation? Not really thinking about memcached in this situation as that can be applied to much more than just this.

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  • Memory efficient int-int dict in Python

    - by Bolo
    Hi, I need a memory efficient int-int dict in Python that would support the following operations in O(log n) time: d[k] = v # replace if present v = d[k] # None or a negative number if not present I need to hold ~250M pairs, so it really has to be tight. Do you happen to know a suitable implementation (Python 2.7)? EDIT Removed impossible requirement and other nonsense. Thanks, Craig and Kylotan! To rephrase. Here's a trivial int-int dictionary with 1M pairs: >>> import random, sys >>> from guppy import hpy >>> h = hpy() >>> h.setrelheap() >>> d = {} >>> for _ in xrange(1000000): ... d[random.randint(0, sys.maxint)] = random.randint(0, sys.maxint) ... >>> h.heap() Partition of a set of 1999530 objects. Total size = 49161112 bytes. Index Count % Size % Cumulative % Kind (class / dict of class) 0 1 0 25165960 51 25165960 51 dict (no owner) 1 1999521 100 23994252 49 49160212 100 int On average, a pair of integers uses 49 bytes. Here's an array of 2M integers: >>> import array, random, sys >>> from guppy import hpy >>> h = hpy() >>> h.setrelheap() >>> a = array.array('i') >>> for _ in xrange(2000000): ... a.append(random.randint(0, sys.maxint)) ... >>> h.heap() Partition of a set of 14 objects. Total size = 8001108 bytes. Index Count % Size % Cumulative % Kind (class / dict of class) 0 1 7 8000028 100 8000028 100 array.array On average, a pair of integers uses 8 bytes. I accept that 8 bytes/pair in a dictionary is rather hard to achieve in general. Rephrased question: is there a memory-efficient implementation of int-int dictionary that uses considerably less than 49 bytes/pair?

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  • The best way to implement drawing features like Keynote

    - by Shamseddine
    Hi all, I'm trying to make a little iPad tool's for drawing simple geometrical objects (rect, rounded rect, ellipse, star, ...). My goal is to make something very close to Keynote (drawing feature), i.e. let the user add a rect (for instance), resizing it and moving it. I want too the user can select many objects and move them together. I've thought about at least 3 differents ways to do that : Extends UIView for each object type, a class for Rect, another for Ellipse, ... With custom drawing method. Then add this view as subview of the global view. Extends CALayer for each object type, a class for Rect, another for Ellipse, ... With custom drawing method. Then add this layer as sublayer of the global view layer's. Extends NSObject for each object type, a class for Rect, another for Ellipse, ... With just a drawing method which will get as argument a CGContext and a Rect and draw directly the form in it. Those methods will be called by the drawing method of the global view. I'm aware that the two first ways come with functions to detect touch on each object, to add easily shadows,... but I'm afraid that they are a little too heavy ? That's why I thought about the last way, which it seems to be straight forward. Which way will be the more efficient ??? Or maybe I didn't thought another way ? Any help will be appreciated ;-) Thanks.

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  • PHP Increasing write to page speed.

    - by Frederico
    I'm currently writing out xml and have done the following: header ("content-type: text/xml"); header ("content-length: ".strlen($xml)); $xml being the xml to be written out. I'm near about 1.8 megs of text (which I found via firebug), it seems as the writing is taking more time than the script to run.. is there a way to increase this write speed? Thank you in advance.

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  • Webcrawler, feedback?

    - by Jan Kuboschek
    Hey folks, every once in a while I have the need to automate data collection tasks from websites. Sometimes I need a bunch of URLs from a directory, sometimes I need an XML sitemap (yes, I know there is lots of software for that and online services). Anyways, as follow up to my previous question I've written a little webcrawler that can visit websites. Basic crawler class to easily and quickly interact with one website. Override "doAction(String URL, String content)" to process the content further (e.g. store it, parse it). Concept allows for multi-threading of crawlers. All class instances share processed and queued lists of links. Instead of keeping track of processed links and queued links within the object, a JDBC connection could be established to store links in a database. Currently limited to one website at a time, however, could be expanded upon by adding an externalLinks stack and adding to it as appropriate. JCrawler is intended to be used to quickly generate XML sitemaps or parse websites for your desired information. It's lightweight. Is this a good/decent way to write the crawler, provided the limitations above? http://pastebin.com/VtgC4qVE - Main.java http://pastebin.com/gF4sLHEW - JCrawler.java http://pastebin.com/VJ1grArt - HTMLUtils.java Thanks for your feedback in advance! :)

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  • How to optimise MySQL query containing a subquery?

    - by aidan
    I have two tables, House and Person. For any row in House, there can be 0, 1 or many corresponding rows in Person. But, of those people, a maximum of one will have a status of "ACTIVE", the others will all have a status of "CANCELLED". e.g. SELECT * FROM House LEFT JOIN Person ON House.ID = Person.HouseID House.ID | Person.ID | Person.Status 1 | 1 | CANCELLED 1 | 2 | CANCELLED 1 | 3 | ACTIVE 2 | 1 | ACTIVE 3 | NULL | NULL 4 | 4 | CANCELLED I want to filter out the cancelled rows, and get something like this: House.ID | Person.ID | Person.Status 1 | 3 | ACTIVE 2 | 1 | ACTIVE 3 | NULL | NULL 4 | NULL | NULL I've achieved this with the following sub select: SELECT * FROM House LEFT JOIN ( SELECT * FROM Person WHERE Person.Status != "CANCELLED" ) Person ON House.ID = Person.HouseID ...which works, but breaks all the indexes. Is there a better solution that doesn't? I'm using MySQL and all relevant columns are indexed. EXPLAIN lists nothing in possible_keys. Thanks.

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