bit-manipulation

I am trying to make a loop that loops through all different integers where exactly 10 of the last 40 bits are set high, the rest set low. The reason is that I have a map with 40 different values, and I want to sum all different ways ten of these values can be multiplied. (This is just out of curiosity, so it's really the "bitmanip"-loop that is of interest, not the sum as such.) If I were to do this with e.g. 2 out of 4 bits, it would be easy to set all manually, 0011 = 3, 0101 = 5, 1001 = 9, 0110 = 6, 1010 = 10, 1100 = 12, but with 10 out of 40 I can't seem to find a method to generate these

I've been trying to extend the xor-swap to more than two variables, say n variables. But I've gotten nowhere that's better than 3*(n-1) . For two integer variables x1 and x2 you can swap them like this: swap(x1,x2) { x1 = x1 ^ x2; x2 = x1 ^ x2; x1 = x1 ^ x2; } So, assume you have x1 ... xn with values v1 ... vn . Clearly you can "rotate" the values by successively applying swap: swap(x1,x2); swap(x2,x3); swap(x3,x4); ... swap(xm,xn); // with m = n-1 You will end up with x1 = v2 , x2 = v3 , ..., xn = v1 . Which costs n-1 swaps, each costing 3 xors, leaving us with (n-1)*3 xors. Is a faster

Is there an efficient (fast) algorithm that will perform bit expansion/duplication? For example, expand each bit in an 8bit value by 3 (creating a 24bit value): 1101 0101 => 11111100 01110001 11000111 The brute force method that has been proposed is to create a lookup table. In the future, the expansion value may need to be variable. That is, in the above example we are expanding by 3 but may need to expand by some other value(s). This would require multiple lookup tables that I'd like to avoid if possible. There is a chance to make it quicker than lookup table if arithmetic calculations are

Abstract Hi, suppose you have two different independent 64-bit binary matrices A and T ( T is a transposed version of itself, using the transposed version of matrix allows during multiplication to operate on T 's rows rather than columns which is super cool for binary arithmetic) and you want to multiply these matrices the only thing is that matrix multiplication result is truncated to 64-bits and if you yield to a value greater that 1 in some specific matrix cell the resulting matrix cell will contain 1 otherwise 0 Example A T 00000001 01111101 01010100 01100101 10010111 00010100 10110000