computation

I want to find optimal parameters i, j, k in 0..99 for a given computational problem, and I need to run: for i in range(100): for j in range(100): for k in range(100): dothejob(i, j, k) # 1 second per computation This takes a total of 10^6 seconds, i.e. 11.5 days. I started doing it by splitting the work among 4 processes (to use 100% computing power of my 4-core CPU computer): for i in range(100): if i % 4 != 0: # replace != 0 by 1, 2, or 3 for the parallel scripts #2, #3, #4 continue for j in range(100): for k in range(100): dothejob(i, j, k) with open('done.log', 'a+') as f: # log what has

I have a round robin tournament where I create all the games necessary (7 games per participant) for 8 teams. I however need 10 games per participant which means I need to duplicate matchups, and on top of that 1 and 5 can't play each other. You can see from the data below the games I generated for each participant (# of games) in the order it was created which would be the round. I am trying to figure out the best possible way to duplicate the matchups and evently distribute the matchups in such a way that there aren't matchups that duplicate three times and still retain 10 games per

As far as I know, a Turing machine can be made to execute loops or iterations of instructions encoded on a Tape. This can be done by identifying Line separators and making the Turing machine go back until a specific count of Line separators is reached (that is, inside the loop). But, can a Turing machine also execute a recursive program? Can someone describe various details for such a Turing Machine? I suppose, if recursion can be executed by a Turing machine, the Quicksort can also be performed? If the question is if a Turing Machine can execute a sorting algorithm, the answer is yes, since

I looking for the information about fast GCD computation algorithms. Especially, I would like to take a look at the realizations of that. The most interesting for me: - Lehmer GCD algorithm, - Accelerated GCD algorithm, - k-ary algorithm, - Knuth-Schonhage with FFT. I have completely NO information about the accelerated GCD algorithm, I just have seen a few articles where it was mentioned as the most effective and fast gcd computation method on the medium inputs (~1000 bits) They looks much difficult for me to understand from the theory view. Could anybody please share the code (preferable on

I'm currently developing a math application that makes long computations. I'm getting java.lang.NumberFormatException: Invalid int: "..." error (where the ... is replaced by a very long number) whenever I type an integer that contains more than 9 digits. When I type in an integer that is less than or equal to 9 digits, the application runs fine. I need the output to be an int (i.e. no decimal places). Not quite sure why the error's occurring. The bit of code that's causing the problem is: Intent intent = getIntent(); String message = intent.getStringExtra(MainActivity.NUMBER); int inp =

For example I want to calculate (reasonably efficiently) 2^1000003 mod 12321 And finally I want to do (2^1000003 - 3) mod 12321. Is there any feasible way to do this? Basic modulo properties tell us that 1) a + b (mod n) is (a (mod n)) + (b (mod n)) (mod n) , so you can split the operation in two steps 2) a * b (mod n) is (a (mod n)) * (b (mod n)) (mod n) , so you can use modulo exponentiation (pseudocode): x = 1 for (10000003 times) { x = (x * 2) % 12321; # x will never grow beyond 12320 } Of course, you shouldn't do 10000003 iterations, just remember that 2 1000003 = 2 * 2 1000002 , and 2