Efficient way to find divisibility - c

Professor says this isn't a efficient algorithm to check whether the number is divisible by a number from 100,000-150,000. I'm having trouble finding a better way. Any help would be appreciated.
unsigned short divisibility_check(unsigned long n) {
unsigned long i;
for (i = 100000; i <= 150000; i++) {
if (n % i == 0) {
return 0;
}
}
return 1;
}

Let's say you need to find whether a positive integer K is divisible by a number between 100,000 and 150,000, and it is such a rare operation, that doing precalculations is just not worth the processor time or memory used.
If K < 100,000, it cannot be divisible by a number between 100,000 and 150,000.
If 100,000 ≤ K ≤ 150,000, it is divisible by itself. It is up to you to decide whether this counts or not.
For a K > 150,000 to be divisible by M, with 100,000 ≤ M ≤ 150,000, K must also be divisible by L = K / M. This is because K = L × M, and all three are positive integers. So, you only need to test the divisibility of K by a set of L, where ⌊ K / 150,000 ⌋ ≤ L ≤ ⌊ K / 100,000 ⌋.
However, that set of Ls becomes larger than the set of possible Ms when K > = 15,000,000,000. Then it is again less work to just test K for divisibility against each M, much like OP's code is now.
When implementing this as a program, the most important thing in practice is, surprisingly, the comments you add. Do not write comments that describe what the code does; write comments that explain the model or algorithm you are trying to implement (say, at the function level), and your intent of what each small block of code should accomplish.
In this particular case, you should probably add a comment to each if clause, explaining your reasoning, much like I did above.
Beginner programmers often omit comments completely. It is unfortunate, because writing good comments is a hard habit to pick up afterwards. It is definitely a good idea to learn to comment your code (as I described above -- the comments that describe what the code does are less than useful; more noise than help), and keep honing your skill on that.
A programmer whose code is maintainable, is worth ten geniuses who produce write-only code. This is because all code has bugs, because humans make errors. To be an efficient developer, your code must be maintainable. Otherwise you're forced to rewrite each buggy part from scratch, wasting a lot of time. And, as you can see above, "optimization" at the algorithmic level, i.e. thinking about how to avoid having to do work, yields much better results than trying to optimize your loops or something like that. (You'll find in real life that surprisingly often, optimizing a loop in the proper way, removes the loop completely.)
Even in exercises, proper comments may be the difference between "no points, this doesn't work" and "okay, I'll give you partial credit for this one, because you had a typo/off-by-one bug/thinko on line N, but otherwise your solution would have worked".
As bolov did not understand how the above leads to a "naive_with_checks" function, I'll show it implemented here.
For ease of testing, I'll show a complete test program. Supply the range of integers to test, and the range of divisors accepted, as parameters to the program (i.e. thisprogram 1 500000 100000 150000 to duplicate bolov's tests).
#include <stdlib.h>
#include <inttypes.h>
#include <limits.h>
#include <locale.h>
#include <ctype.h>
#include <stdio.h>
#include <errno.h>
int is_divisible(const uint64_t number,
const uint64_t minimum_divisor,
const uint64_t maximum_divisor)
{
uint64_t divisor, minimum_result, maximum_result, result;
if (number < minimum_divisor) {
return 0;
}
if (number <= maximum_divisor) {
/* Number itself is a valid divisor. */
return 1;
}
minimum_result = number / maximum_divisor;
if (minimum_result < 2) {
minimum_result = 2;
}
maximum_result = number / minimum_divisor;
if (maximum_result < minimum_result) {
maximum_result = minimum_result;
}
if (maximum_result - minimum_result > maximum_divisor - minimum_divisor) {
/* The number is so large that it is the least amount of work
to check each possible divisor. */
for (divisor = minimum_divisor; divisor <= maximum_divisor; divisor++) {
if (number % divisor == 0) {
return 1;
}
}
return 0;
} else {
/* There are fewer possible results than divisors,
so we check the results instead. */
for (result = minimum_result; result <= maximum_result; result++) {
if (number % result == 0) {
divisor = number / result;
if (divisor >= minimum_divisor && divisor <= maximum_divisor) {
return 1;
}
}
}
return 0;
}
}
int parse_u64(const char *s, uint64_t *to)
{
unsigned long long value;
const char *end;
/* Empty strings are not valid. */
if (s == NULL || *s == '\0')
return -1;
/* Parse as unsigned long long. */
end = s;
errno = 0;
value = strtoull(s, (char **)(&end), 0);
if (errno == ERANGE)
return -1;
if (end == s)
return -1;
/* Overflow? */
if (value > UINT64_MAX)
return -1;
/* Skip trailing whitespace. */
while (isspace((unsigned char)(*end)))
end++;
/* If the string does not end here, it has garbage in it. */
if (*end != '\0')
return -1;
if (to)
*to = (uint64_t)value;
return 0;
}
int main(int argc, char *argv[])
{
uint64_t kmin, kmax, dmin, dmax, k, count;
if (argc != 5) {
fprintf(stderr, "\n");
fprintf(stderr, "Usage: %s [ -h | --help | help ]\n", argv[0]);
fprintf(stderr, " %s MIN MAX MIN_DIVISOR MAX_DIVISOR\n", argv[0]);
fprintf(stderr, "\n");
fprintf(stderr, "This program counts which positive integers between MIN and MAX,\n");
fprintf(stderr, "inclusive, are divisible by MIN_DIVISOR to MAX_DIVISOR, inclusive.\n");
fprintf(stderr, "\n");
return EXIT_SUCCESS;
}
/* Use current locale. This may change which codes isspace() considers whitespace. */
if (setlocale(LC_ALL, "") == NULL)
fprintf(stderr, "Warning: Your C library does not support your current locale.\n");
if (parse_u64(argv[1], &kmin) || kmin < 1) {
fprintf(stderr, "%s: Invalid minimum positive integer to test.\n", argv[1]);
return EXIT_FAILURE;
}
if (parse_u64(argv[2], &kmax) || kmax < kmin || kmax >= UINT64_MAX) {
fprintf(stderr, "%s: Invalid maximum positive integer to test.\n", argv[2]);
return EXIT_FAILURE;
}
if (parse_u64(argv[3], &dmin) || dmin < 2) {
fprintf(stderr, "%s: Invalid minimum divisor to test for.\n", argv[3]);
return EXIT_FAILURE;
}
if (parse_u64(argv[4], &dmax) || dmax < dmin) {
fprintf(stderr, "%s: Invalid maximum divisor to test for.\n", argv[4]);
return EXIT_FAILURE;
}
count = 0;
for (k = kmin; k <= kmax; k++)
count += is_divisible(k, dmin, dmax);
printf("%" PRIu64 "\n", count);
return EXIT_SUCCESS;
}
It is useful to note that the above, running bolov's test, i.e. thisprogram 1 500000 100000 150000 only takes about 15 ms of wall clock time (13 ms CPU time), median, on a much slower Core i5-7200U processor. For really large numbers, like 280,000,000,000 to 280,000,010,000, the test does the maximum amount of work, and takes about 3.5 seconds per 10,000 numbers on this machine.
In other words, I wouldn't trust bolov's numbers to have any relation to timings for properly written test cases.
It is important to note that for any K between 1 and 500,000, the same test that bolov says their code measures, the above code does at most two divisibility tests to find if K is divisible by an integer between 100,000 and 150,000.
This solution is therefore quite efficient. It is definitely acceptable and near-optimal, when the tested K are relatively small (say, 32 bit unsigned integers or smaller), or when precomputed tables cannot be used.
Even when precomputed tables can be used, it is unclear if/when prime factorization becomes faster than the direct checks. There is certainly a tradeoff in the size and content of the precomputed tables. bolov claims that it is clearly superior to other methods, but hasn't implemented a proper "naive" divisibility test as shown above, and bases their opinion on experiments on quite small integers (1 to 500,000) that have simple prime decompositions.
As an example, a table of integers 1 to 500,000 pre-checked for divisibility takes only 62500 bytes (43750 bytes for 150,000 to 500,000). With that table, each test takes a small near-constant time (that only depends on memory and cache effects). Extending it to all 32-bit unsigned integers would require 512 GiB (536,870,912 bytes); the table can be stored in a memory-mapped read-only file, to let the OS kernel manage how much of it is mapped to RAM at any time.
Prime decomposition itself, especially using trial division, becomes more expensive than the naive approach when the number of trial divisions exceeds the range of possible divisors (50,000 divisors in this particular case). As there are 13848 primes (if one counts 1 and 2 as primes) between 1 and 150,000, the number of trial divisions can easily approach the number of divisors for sufficiently large input values.
For numbers with many prime factors, the combinatoric phase, finding if any subset of the prime factors multiply to a number between 100,000 and 150,000 is even more problematic. The number of possible combinations grows faster than exponentially. Without careful checks, this phase alone can do way more work per large input number than just trial division with each possible divisor would be.
(As an example, if you have 16 different prime factors, you already have 65,535 different combinations; more than the number of direct trial divisions. However, all such numbers are larger than 64-bit; the smallest being 2·3·5·7·11·13·17·19·23·29·31·37·41·43·47·53 = 32,589,158,477,190,044,730 which is a 65-bit number.)
There is also the problem of code complexity. The more complex the code, the harder it is to debug and maintain.

Ok, so I've implemented the version with sieve primes and factorization mentioned in the comments by m69 and it is ... way faster than the naive approach. I must admit, I didn't expect this at all.
My notations: left == 100'000 and right = 150'000
naive your version
naive_with_checks your version with simple checks:
if (n < left) no divisor
else if (n <= right) divisor
else if (left * 2 >= right && n < left * 2) divisor
factorization (above checks implemented)
Precompute the Sieve of Eratosthenes for all primes up to right. This time is not measured
factorize n (only with the primes from the prev step)
generate all subsets (backtracking, depth first: i.e. generate p1^0 * p2^0 * p3^0 first, instead of p1^5 first) with the product < left or until the product is in [left, right] (found divisor).
factorization_opt optimization of the previous algorithm where the subsets are not generated (no vector of subsets is created). I just pass the current product from one backtracking iteration to the next.
Nominal Animal's version I have also ran his version on my system with the same range.
I have written the program in C++ so I won't share it here.
I used std::uint64_t as data type and I have checked all numbers from 1 to 500'000 to see if each is divisible by a number in interval [100'000, 150'000]. All version reached the same solution: 170'836 numbers with positive results.
The setup:
Hardware: Intel Core i7-920, 4 cores with HT (all algorithm versions are single threaded), 2.66 GHz (boost 2.93 GHz),
8 MB SmartCache; memory: 6 GB DDR3 triple channel.
Compiler: Visual Studio 2017 (v141), Release x64 mode.
I must also add that I haven't profiled the programs so there is definitely room to improve the implementation. However this is enough here as the idea is to find a better algorithm.
version | elapsed time (milliseconds)
-----------------------+--------------
naive         |  167'378 ms (yes, it's thousands separator, aka 167 seconds)
naive_with_checks |   97'197 ms
factorization | 7'906 ms
factorization_opt | 7'320 ms
|
Nominal Animal version | 14 ms
Some analysis:
For naive vs naive_with_checks: all the numbers in [1 200'000] can be solved with just the simple checks. As these represent 40% of all the numbers checked, the naive_with_checks version does roughly 60% of the work naive does. The execution time reflect this as naive_with_checks runtime is ≅58% of the naive version.
The factorization version is a whopping 12.3 times faster. That is indeed impressive. I haven't analyzed the time complexity of the alg.
And the final optimization brings a further 1.08x speedup. This is basically the time gained by removing the creation and copy of the small vectors of subset factors.
For those interested the sieve precomputation which is not included above takes about 1 ms. And this is the naive implementation from wikipedia, no optimizations whatsoever.

For comparison, here's what I had in mind when I posted my comment about using prime factorization. Compiled with gcc -std=c99 -O3 -m64 -march=haswell this is slightly faster than the naive method with checks and inversion when tested with the last 10,000 integers in the 64-bit range (3.469 vs 3.624 seconds).
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <stdint.h>
#include <stdbool.h>
void eratosthenes(bool *ptr, uint64_t size) {
memset(ptr, true, size);
for (uint64_t i = 2; i * i < size; i++) {
if (ptr[i]) {
for (uint64_t j = i * i; j < size; j += i) {
ptr[j] = false;
}
}
}
}
bool divisible(uint64_t n, uint64_t a, uint64_t b) {
/* check for trivial cases first */
if (n < a) {
return false;
}
if (n <= b) {
return true;
}
if (n < 2 * a) {
return false;
}
/* Inversion: use range n/b ~ n/a; see Nominal Animal's answer */
if (n < a * b) {
uint64_t c = a;
a = (n + b - 1) / b; // n/b rounded up
b = n / c;
}
/* Create prime sieve when first called, or re-calculate it when */
/* called with a higher value of b; place before inversion in case */
/* of a large sequential test, to avoid repeated re-calculation. */
static bool *prime = NULL;
static uint64_t prime_size = 0;
if (prime_size <= b) {
prime_size = b + 1;
prime = realloc(prime, prime_size * sizeof(bool));
if (!prime) {
printf("Out of memory!\n");
return false;
}
eratosthenes(prime, prime_size);
}
/* Factorize n into prime factors up to b, using trial division; */
/* there are more efficient but also more complex ways to do this. */
/* You could return here, if a factor in the range a~b is found. */
static uint64_t factor[63];
uint8_t factors = 0;
for (uint64_t i = 2; i <= n && i <= b; i++) {
if (prime[i]) {
while (n % i == 0) {
factor[factors++] = i;
n /= i;
}
}
}
/* Prepare divisor sieve when first called, or re-allocate it when */
/* called with a higher value of b; in a higher-level language, you */
/* would probably use a different data structure for this, because */
/* this method iterates repeatedly over a potentially sparse array. */
static bool *divisor = NULL;
static uint64_t div_size = 0;
if (div_size <= b / 2) {
div_size = b / 2 + 1;
divisor = realloc(divisor, div_size * sizeof(bool));
if (!divisor) {
printf("Out of memory!\n");
return false;
}
}
memset(divisor, false, div_size);
divisor[1] = true;
uint64_t max = 1;
/* Iterate over each prime factor, and for every divisor already in */
/* the sieve, add the product of the divisor and the factor, up to */
/* the value b/2. If the product is in the range a~b, return true. */
for (uint8_t i = 0; i < factors; i++) {
for (uint64_t j = max; j > 0; j--) {
if (divisor[j]) {
uint64_t product = factor[i] * j;
if (product >= a && product <= b) {
return true;
}
if (product < div_size) {
divisor[product] = true;
if (product > max) {
max = product;
}
}
}
}
}
return false;
}
int main() {
uint64_t count = 0;
for (uint64_t n = 18446744073709541615LLU; n <= 18446744073709551614LLU; n++) {
if (divisible(n, 100000, 150000)) ++count;
}
printf("%llu", count);
return 0;
}
And this is the naive + checks + inversion implementation I compared it with:
#include <stdio.h>
#include <stdint.h>
#include <stdbool.h>
bool divisible(uint64_t n, uint64_t a, uint64_t b) {
if (n < a) {
return false;
}
if (n <= b) {
return true;
}
if (n < 2 * a) {
return false;
}
if (n < a * b) {
uint64_t c = a;
a = (n + b - 1) / b;
b = n / c;
}
while (a <= b) {
if (n % a++ == 0) return true;
}
return false;
}
int main() {
uint64_t count = 0;
for (uint64_t n = 18446744073709541615LLU; n <= 18446744073709551614LLU; n++) {
if (divisible(n, 100000, 150000)) ++count;
}
printf("%llu", count);
return 0;
}

Here's a recursive method with primes. The idea here is that if a number is divisible by a number between 100000 and 150000, there is a path of reducing by division the product of only relevant primes that will pass through a state in the target range. (Note: the code below is meant for numbers greater than 100000*150000). In my testing, I could not find an instance where the stack performed over 600 iterations.
# Euler sieve
def getPrimes():
n = 150000
a = (n+1) * [None]
ps = ([],[])
s = []
p = 1
while (p < n):
p = p + 1
if not a[p]:
s.append(p)
# Save primes less
# than half
# of 150000, the only
# ones needed to construct
# our candidates.
if p < 75000:
ps[0].append(p);
# Save primes between
# 100000 and 150000
# in case our candidate
# is prime.
elif p > 100000:
ps[1].append(p)
limit = n / p
new_s = []
for i in s:
j = i
while j <= limit:
new_s.append(j)
a[j*p] = True
j = j * p
s = new_s
return ps
ps1, ps2 = getPrimes()
def f(n):
# Prime candidate
for p in ps2:
if not (n % p):
return True
# (primes, prime_counts)
ds = ([],[])
prod = 1
# Prepare only prime
# factors that could
# construct a composite
# candidate.
for p in ps1:
while not (n % p):
prod *= p
if (not ds[0] or ds[0][-1] != p):
ds[0].append(p)
ds[1].append(1)
else:
ds[1][-1] += 1
n /= p
# Reduce the primes product to
# a state where it's between
# our target range.
stack = [(prod,0)]
while stack:
prod, i = stack.pop()
# No point in reducing further
if prod < 100000:
continue
# Exit early
elif prod <= 150000:
return True
# Try reducing the product
# by different prime powers
# one prime at a time
if i < len(ds[0]):
for p in xrange(ds[1][i] + 1):
stack.append((prod / ds[0][i]**p, i + 1))
return False
Output:
c = 0
for ii in xrange(1099511627776, 1099511628776):
f_i = f(ii)
if f_i:
c += 1
print c # 239

Here is a very simple solution with a sieve cache. If you call the divisibility_check function for many numbers in a sequence, this should be very efficient:
#include <string.h>
int divisibility_check_sieve(unsigned long n) {
static unsigned long sieve_min = 1, sieve_max;
static unsigned char sieve[1 << 19]; /* 1/2 megabyte */
if (n < sieve_min || n > sieve_max) {
sieve_min = n & ~(sizeof(sieve) - 1);
sieve_max = sieve_min + sizeof(sieve) - 1;
memset(sieve, 1, sizeof sieve);
for (unsigned long m = 100000; m <= 150000; m++) {
unsigned long i = sieve_min % m;
if (i != 0)
i = m - i;
for (; i < sizeof sieve; i += m) {
sieve[i] = 0;
}
}
}
return sieve[n - sieve_min];
}
Here is a comparative benchmark:
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <time.h>
int divisibility_check_naive(unsigned long n) {
for (unsigned long i = 100000; i <= 150000; i++) {
if (n % i == 0) {
return 0;
}
}
return 1;
}
int divisibility_check_small(unsigned long n) {
unsigned long i, min = n / 150000, max = n / 100000;
min += (min == 0);
max += (max == 0);
if (max - min > 150000 - 100000) {
for (i = 100000; i <= 150000; i++) {
if (n % i == 0) {
return 0;
}
}
return 1;
} else {
for (i = min; i <= max; i++) {
if (n % i == 0) {
unsigned long div = n / i;
if (div >= 100000 && div <= 150000)
return 0;
}
}
return 1;
}
}
int divisibility_check_sieve(unsigned long n) {
static unsigned long sieve_min = 1, sieve_max;
static unsigned char sieve[1 << 19]; /* 1/2 megabyte */
if (n < sieve_min || n > sieve_max) {
sieve_min = n & ~(sizeof(sieve) - 1);
sieve_max = sieve_min + sizeof(sieve) - 1;
memset(sieve, 1, sizeof sieve);
for (unsigned long m = 100000; m <= 150000; m++) {
unsigned long i = sieve_min % m;
if (i != 0)
i = m - i;
for (; i < sizeof sieve; i += m) {
sieve[i] = 0;
}
}
}
return sieve[n - sieve_min];
}
int main(int argc, char *argv[]) {
unsigned long n, count = 0, lmin, lmax, range[2] = { 1, 500000 };
int pos = 0, naive = 0, small = 0, sieve = 1;
clock_t t;
char *p;
for (int i = 1; i < argc; i++) {
n = strtoul(argv[i], &p, 0);
if (*p == '\0' && pos < 2)
range[pos++] = n;
else if (!strcmp(argv[i], "naive"))
naive = 1;
else if (!strcmp(argv[i], "small"))
small = 1;
else if (!strcmp(argv[i], "sieve"))
sieve = 1;
else
printf("invalid argument: %s\n", argv[i]);
}
lmin = range[0];
lmax = range[1] + 1;
if (naive) {
t = clock();
for (count = 0, n = lmin; n != lmax; n++) {
count += divisibility_check_naive(n);
}
t = clock() - t;
printf("naive: [%lu..%lu] -> %lu non-divisible numbers, %10.2fms\n",
lmin, lmax - 1, count, t * 1000.0 / CLOCKS_PER_SEC);
}
if (small) {
t = clock();
for (count = 0, n = lmin; n != lmax; n++) {
count += divisibility_check_small(n);
}
t = clock() - t;
printf("small: [%lu..%lu] -> %lu non-divisible numbers, %10.2fms\n",
lmin, lmax - 1, count, t * 1000.0 / CLOCKS_PER_SEC);
}
if (sieve) {
t = clock();
for (count = 0, n = lmin; n != lmax; n++) {
count += divisibility_check_sieve(n);
}
t = clock() - t;
printf("sieve: [%lu..%lu] -> %lu non-divisible numbers, %10.2fms\n",
lmin, lmax - 1, count, t * 1000.0 / CLOCKS_PER_SEC);
}
return 0;
}
Here are some run times:
naive: [1..500000] -> 329164 non-divisible numbers, 158174.52ms
small: [1..500000] -> 329164 non-divisible numbers, 12.62ms
sieve: [1..500000] -> 329164 non-divisible numbers, 1.35ms
sieve: [0..4294967295] -> 3279784841 non-divisible numbers, 8787.23ms
sieve: [10000000000000000000..10000000001000000000] -> 765978176 non-divisible numbers, 2205.36ms

Related

How to Optimise my code that computes the sum of all from less than 2 million

I've tried this problem from Project Euler where I need to calculate the sum of all primes until two million.
This is the solution I've come up with -
#include <stdio.h>
int main() {
long sum = 5; // Already counting 2 and 3 in my sum.
int i = 5; // Checking from 5
int count = 0;
while (i <= 2000000) {
count = 0;
for (int j = 3; j <= i / 2; j += 2) {
// Checking if i (starting from 5) is divisible from 3
if (i % j == 0) { // to i/2 and only checking for odd values of j
count = 1;
}
}
if (count == 0) {
sum += i;
}
i += 2;
}
printf("%ld ", sum);
}
It takes around 480 secs to run and I was wondering if there was a better solution or tips to improve my program.
________________________________________________________
Executed in 480.95 secs fish external
usr time 478.54 secs 0.23 millis 478.54 secs
sys time 1.28 secs 6.78 millis 1.28 secs
With two little modifications your code becomes magnitudes faster:
#include <stdio.h>
#include <math.h>
int main() {
long long sum = 5; // we need long long, long might not be enough
// depending on your platform
int i = 5;
int count = 0;
while (i <= 2000000) {
count = 0;
int limit = sqrt(i); // determine upper limit once and for all
for (int j = 3; j <= limit; j += 2) { // use upper limit sqrt(i) instead if i/2
if (i % j == 0) {
count = 1;
break; // break out from loop as soon
// as number is not prime
}
}
if (count == 0) {
sum += i;
}
i += 2;
}
printf("%lld ", sum); // we need %lld for long long
}
All explanations are in the comments.
But there are certainly better and even faster ways to do this.
I ran this on my 10 year old MacPro and for the 20 million first primes it took around 30 seconds.
This program computes near instantly (even in Debug...) the sum for 2 millions, just need one second for 20 millions (Windows 10, 10 years-old i7 # 3.4 GHz, MSVC 2019).
Note: Didn't had time to set up my C compiler, it's why there is a cast on the malloc.
The "big" optimization is to store square values AND prime numbers, so absolutely no impossible divisor is tested. Since there is no more than 1/10th of primes within a given integer interval (heuristic, a robust code should test that and realloc the primes array when needed), the time is drastically cut.
#include <stdio.h>
#include <malloc.h>
#define LIMIT 2000000ul // Computation limit.
typedef struct {
unsigned long int p ; // Store a prime number.
unsigned long int sq ; // and its square.
} prime ;
int main() {
prime* primes = (prime*)malloc((LIMIT/10)*sizeof(*primes)) ; // Store found primes. Can quite safely use 1/10th of the whole computation limit.
unsigned long int primes_count=1 ;
unsigned long int i = 3 ;
unsigned long long int sum = 0 ;
unsigned long int j = 0 ;
int is_prime = 1 ;
// Feed the first prime, 2.
primes[0].p = 2 ;
primes[0].sq = 4 ;
sum = 2 ;
// Parse all numbers up to LIMIT, ignoring even numbers.
// Also reset the "is_prime" flag at each loop.
for (i = 3 ; i <= LIMIT ; i+=2, is_prime = 1 ) {
// Parse all previously found primes.
for (j = 0; j < primes_count; j++) {
// Above sqrt(i)? Break, i is a prime.
if (i<primes[j].sq)
break ;
// Found a divisor? Not a prime (and break).
if ((i % primes[j].p == 0)) {
is_prime = 0 ;
break ;
}
}
// Add the prime and its square to the array "primes".
if (is_prime) {
primes[primes_count].p = i ;
primes[primes_count++].sq = i*i ;
// Compute the sum on-the-fly
sum += i ;
}
}
printf("Sum of all %lu primes: %llu\n", primes_count, sum);
free(primes) ;
}
Your program can easily be improved by stopping the inner loop earlier:
when i exceeds sqrt(j).
when a divisor has been found.
Also note that type long might not be large enough for the sum on all architectures. long long is recommended.
Here is a modified version:
#include <stdio.h>
int main() {
long long sum = 5; // Already counting 2 and 3 in my sum.
long i = 5; // Checking from 5
while (i <= 2000000) {
int count = 0;
for (int j = 3; j * j <= i; j += 2) {
// Checking if i (starting from 5) is divisible from 3
if (i % j == 0) { // to i/2 and only checking for odd values of j
count = 1;
break;
}
}
if (count == 0) {
sum += i;
}
i += 2;
}
printf("%lld\n", sum);
}
This simple change drastically reduces the runtime! It is more than 1000 times faster for 2000000:
chqrlie> time ./primesum
142913828922
real 0m0.288s
user 0m0.264s
sys 0m0.004s
Note however that trial division is much less efficient than the classic sieve of Eratosthenes.
Here is a simplistic version:
#include <stdio.h>
#include <stdlib.h>
int main() {
long max = 2000000;
long long sum = 0;
// Allocate an array of indicators initialized to 0
unsigned char *composite = calloc(1, max + 1);
// For all numbers up to sqrt(max)
for (long i = 2; i * i <= max; i++) {
// It the number is a prime
if (composite[i] == 0) {
// Set all multiples as composite. Multiples below the
// square of i are skipped because they have already been
// set as multiples of a smaller prime.
for (long j = i * i; j <= max; j += i) {
composite[j] = 1;
}
}
}
for (long i = 2; i <= max; i++) {
if (composite[i] == 0)
sum += i;
}
printf("%lld\n", sum);
free(composite);
return 0;
}
This code is another 20 times faster for 2000000:
chqrlie> time ./primesum-sieve
142913828922
real 0m0.014s
user 0m0.007s
sys 0m0.002s
The sieve approach can be further improved in many ways for larger boundaries.

What is the time complexity of exponentiation by squaring?

Here is a code to exponentiate a number to a given power:
#include <stdio.h>
int foo(int m, int k) {
if (k == 0) {
return 1;
} else if (k % 2 != 0) {
return m * foo(m, k - 1);
} else {
int p = foo(m, k / 2);
return p * p;
}
}
int main() {
int m, k;
while (scanf("%d %d", &m, &k) == 2) {
printf("%d\n", foo(m, k));
}
return 0;
}
How do I calculate the time complexity of the function foo?
I have been able to deduce that if k is a power of 2, the time complexity is O(log k).
But I am finding it difficult to calculate for other values of k. Any help would be much appreciated.
How do I calculate the time complexity of the function foo()?
I have been able to deduce that if k is a power of 2, the time complexity is O(logk).
First, I assume that the time needed for each function call is constant (this would for example not be the case if the time needed for a multiplication depends on the numbers being multiplied - which is the case on some computers).
We also assume that k>=1 (otherwise, the function will run endlessly unless there is an overflow).
Let's think the value k as a binary number:
If the rightmost bit is 0 (k%2!=0 is false), the number is shifted right by one bit (foo(m,k/2)) and the function is called recursively.
If the rightmost bit is 1 (k%2!=0 is true), the bit is changed to a 0 (foo(m,k-1)) and the function is called recursively. (We don't look at the case k=1, yet.)
This means that the function is called once for each bit and it is called once for each 1 bit. Or, in other words: It is called once for each 0 bit in the number and twice for each 1 bit.
If N is the number of function calls, n1 is the number of 1 bits and n0 is the number of 0 bits, we get the following formula:
N = n0 + 2*n1 + C
The constant C (C=(-1), if I didn't make a mistake) represents the case k=1 that we ignored up to now.
This means:
N = (n0 + n1) + n1 + C
And - because n0 + n1 = floor(log2(k)) + 1:
floor(log2(k)) + C <= N <= 2*floor(log2(k)) + C
As you can see, the time complexity is always O(log(k))
O(log(k))
Some modification added to output a statistics for spread sheet plot.
#include <stdio.h>
#include <math.h>
#ifndef TEST_NUM
#define TEST_NUM (100)
#endif
static size_t iter_count;
int foo(int m, int k) {
iter_count++;
if (k == 0) {
return 1;
} else if(k == 1) {
return m;
} else if (k % 2 != 0) {
return m * foo(m, k - 1);
} else {
int p = foo(m, k / 2);
return p * p;
}
}
int main() {
for (int i = 1; i < TEST_NUM; ++i) {
iter_count = 0;
int dummy_result = foo(1, i);
printf("%d, %zu, %f\n", i, iter_count, log2(i));
}
return 0;
}
Build it.
gcc t1.c -DTEST_NUM=10000
./a > output.csv
Now open the output file with a spread sheet program and plot the last two output columns.
For k positive, the function foo calls itself recursively p times if k is the p-th power of 2. If k is not a power of 2, the number of recursive calls is strictly inferior to 2 * p where p is the exponent of the largest power of 2 inferior to k.
Here is a demonstration:
let's expand the recursive call in the case k % 2 != 0:
int foo(int m, int k) {
if (k == 1) {
return m;
} else
if (k % 2 != 0) { /* 2 recursive calls */
// return m * foo(m, k - 1);
int p = foo(m, k / 2);
return m * p * p;
} else { /* 1 recursive call */
int p = foo(m, k / 2);
return p * p;
}
}
The total number of calls is floor(log2(k)) + bitcount(k), and bitcount(k) is by construction <= ceil(log2(k)).
There are no loops in the code and the time of each individual call is bounded by a constant, hence the overall time complexity of O(log k).
The number of times the function is called (recursively or not) per power call is proportional to the minimum number of bits in the exponent required to represent it in binary form.
Each time you enter in the function, it solves by reducing the number by one if the exponent is odd, OR reducing it to half if the exponent is even. This means that we will do n squares per significant bit in the number, and m more multiplications by the base for all the bits that are 1 in the exponent (which are, at most, n, so m < n) for a 32bit significant exponent (this is an exponent between 2^31 and 2^32 the routine will do between 32 and 64 products to get the result, and will reenter to itself a maximum of 64 times)
as in both cases the routine is tail-recursive, the code you post can be substituted with an iterative code in which a while loop is used to solve the problem.
int foo(int m, int k)
{
int prod = 1; /* last recursion foo(m, 0); */
int sq = m; /* squares */
while (k) {
if (k & 1) {
prod *= sq; /* foo(m, k); k odd */
}
k >>= 1;
sq *= sq;
}
return prod; /* return final product */
}
That's huge savings!!! (between 32 multiplications and 64 multiplications, to elevate something to 1,000,000,000 power)

Ramanujan's number in C

[Hardy about Ramanujan]: I remember once going to see him when he was ill at Putney. I had ridden in taxi cab number 1729 and remarked that the number seemed to me rather a dull one, and that I hoped it was not an unfavourable omen. "No," he replied, "it is a very interesting number; it is the smallest number expressible as the sum of two cubes in two different ways."
The two different ways are 1³ + 12³ and 9³ + 10³
I'm writing a series of functions (in C) to calculate different things related to Ramanujan's numbers. I'm now trying to write a function that returns the i-th Ramanujan's number. Since I've already created a function that checks whether a number is a Ramanujan number or not, the easy way would be to check every number, from 0 to infinity. If a given number is a Ramanujan number, increment a counter by one. Once the counter equals the index I'm looking for, I return the number. In code:
unsigned long ramanujan_index (unsigned long x, int counter, int index)
{
if (counter == index)
return x - 1;
if (is_ramanujan(x))
return ramanujan_index(x + 1, counter + 1, index);
else
return ramanujan_index(x + 1, counter, index);
}
It works, sure, but I'm a little worried that it's not as efficient as it could possibly be. Checking every number doesn't seem like the best solution. More so if we consider the first number is 1729, and the second is 4104. It seems that it'd take quite a lot of steps to find the 5th Ramanujan number (32832 steps, actually, since it has to check every number from 0 to 32832, which is the 5th number). Is there a better way to do so?
Here is a simple program using nested loops to enumerate Ramanujan numbers of different orders. It uses an array to store the number of ways and enumerates cubes to generate sums. The computation is performed in slices to take advantage of CPU caches and allow for ranges that exceed memory size.
This program enumerates Ramanujan numbers of order 2 up to 1 million in less than 0.01s and finds the smallest Ramanujan number of order 4 in a few hours: 6963472309248
#include <stdio.h>
#include <stdlib.h>
#define MAX_SLICE 0x400000 // use 4MB at a time
int main(int argc, char **argv) {
int order = 2;
size_t min = 0, max = 1000000, a, a3, b, n, i, n1, n2;
while (*++argv) {
char *p;
n = strtoull(*argv, &p, 0);
if (*p == '-') {
min = n;
max = strtoull(p + 1, NULL, 0);
} else {
if (n < 10)
order = n;
else
max = n;
}
}
for (n1 = min; n1 <= max; n1 = n2) {
size_t slice = (max + 1 - n1 <= MAX_SLICE) ? max + 1 - n1 : MAX_SLICE;
unsigned char *count = calloc(slice, 1);
n2 = n1 + slice;
for (a = 1; (a3 = a * a * a) < n2; a++) {
if (a3 + a3 >= n1) {
for (b = 1; b <= a && (n = a3 + b * b * b) < n2; b++) {
if (n >= n1)
count[n - n1]++;
}
}
}
for (i = n1; i < n2; i++) {
if (count[i - n1] >= order)
printf("%llu\n", (long long unsigned int)i);
}
free(count);
}
return 0;
}
Runs:
chqrlie$ time ./rama
1729
4104
13832
20683
32832
39312
40033
46683
64232
65728
110656
110808
134379
149389
165464
171288
195841
216027
216125
262656
314496
320264
327763
373464
402597
439101
443889
513000
513856
515375
525824
558441
593047
684019
704977
805688
842751
885248
886464
920673
955016
984067
994688
real 0m0.008s
user 0m0.002s
sys 0m0.002s
chqrlie$ time ./rama 10000000000 2 | wc -l
4724
real 0m7.526s
user 0m7.373s
sys 0m0.061s
chqrlie$ time ./rama 6963000000000-6964000000000 4
6963472309248
real 0m10.383s
user 0m10.243s
sys 0m0.050s

Faster algorithm to find how many numbers are not divisible by a given set of numbers

I am trying to solve an online judge problem: http://opc.iarcs.org.in/index.php/problems/LEAFEAT
The problem in short:
If we are given an integer L and a set of N integers s1,s2,s3..sN, we have to find how many numbers there are from 0 to L-1 which are not divisible by any of the 'si's.
For example, if we are given, L = 20 and S = {3,2,5} then there are 6 numbers from 0 to 19 which are not divisible by 3,2 or 5.
L <= 1000000000 and N <= 20.
I used the Inclusion-Exclusion principle to solve this problem:
/*Let 'T' be the number of integers that are divisible by any of the 'si's in the
given range*/
for i in range 1 to N
for all subsets A of length i
if i is odd then:
T += 1 + (L-1)/lcm(all the elements of A)
else
T -= 1 + (L-1)/lcm(all the elements of A)
return T
Here is my code to solve this problem
#include <stdio.h>
int N;
long long int L;
int C[30];
typedef struct{int i, key;}subset_e;
subset_e A[30];
int k;
int gcd(a,b){
int t;
while(b != 0){
t = a%b;
a = b;
b = t;
}
return a;
}
long long int lcm(int a, int b){
return (a*b)/gcd(a,b);
}
long long int getlcm(int n){
if(n == 1){
return A[0].key;
}
int i;
long long int rlcm = lcm(A[0].key,A[1].key);
for(i = 2;i < n; i++){
rlcm = lcm(rlcm,A[i].key);
}
return rlcm;
}
int next_subset(int n){
if(k == n-1 && A[k].i == N-1){
if(k == 0){
return 0;
}
k--;
}
while(k < n-1 && A[k].i == A[k+1].i-1){
if(k <= 0){
return 0;
}
k--;
}
A[k].key = C[A[k].i+1];
A[k].i++;
return 1;
}
int main(){
int i,j,add;
long long int sum = 0,g,temp;
scanf("%lld%d",&L,&N);
for(i = 0;i < N; i++){
scanf("%d",&C[i]);
}
for(i = 1; i <= N; i++){
add = i%2;
for(j = 0;j < i; j++){
A[j].key = C[j];
A[j].i = j;
}
temp = getlcm(i);
g = 1 + (L-1)/temp;
if(add){
sum += g;
} else {
sum -= g;
}
k = i-1;
while(next_subset(i)){
temp = getlcm(i);
g = 1 + (L-1)/temp;
if(add){
sum += g;
} else {
sum -= g;
}
}
}
printf("%lld",L-sum);
return 0;
}
The next_subset(n) generates the next subset of size n in the array A, if there is no subset it returns 0 otherwise it returns 1. It is based on the algorithm described by the accepted answer in this stackoverflow question.
The lcm(a,b) function returns the lcm of a and b.
The get_lcm(n) function returns the lcm of all the elements in A.
It uses the property : LCM(a,b,c) = LCM(LCM(a,b),c)
When I submit the problem on the judge it gives my a 'Time Limit Exceeded'. If we solve this using brute force we get only 50% of the marks.
As there can be upto 2^20 subsets my algorithm might be slow, hence I need a better algorithm to solve this problem.
EDIT:
After editing my code and changing the function to the Euclidean algorithm, I am getting a wrong answer, but my code runs within the time limit. It gives me a correct answer to the example test but not to any other test cases; here is a link to ideone where I ran my code, the first output is correct but the second is not.
Is my approach to this problem correct? If it is then I have made a mistake in my code, and I'll find it; otherwise can anyone please explain what is wrong?
You could also try changing your lcm function to use the Euclidean algorithm.
int gcd(int a, int b) {
int t;
while (b != 0) {
t = b;
b = a % t;
a = t;
}
return a;
}
int lcm(int a, int b) {
return (a * b) / gcd(a, b);
}
At least with Python, the speed differences between the two are pretty large:
>>> %timeit lcm1(103, 2013)
100000 loops, best of 3: 9.21 us per loop
>>> %timeit lcm2(103, 2013)
1000000 loops, best of 3: 1.02 us per loop
Typically, the lowest common multiple of a subset of k of the s_i will exceed L for k much smaller than 20. So you need to stop early.
Probably, just inserting
if (temp >= L) {
break;
}
after
while(next_subset(i)){
temp = getlcm(i);
will be sufficient.
Also, shortcut if there are any 1s among the s_i, all numbers are divisible by 1.
I think the following will be faster:
unsigned gcd(unsigned a, unsigned b) {
unsigned r;
while(b) {
r = a%b;
a = b;
b = r;
}
return a;
}
unsigned recur(unsigned *arr, unsigned len, unsigned idx, unsigned cumul, unsigned bound) {
if (idx >= len || bound == 0) {
return bound;
}
unsigned i, g, s = arr[idx], result;
g = s/gcd(cumul,s);
result = bound/g;
for(i = idx+1; i < len; ++i) {
result -= recur(arr, len, i, cumul*g, bound/g);
}
return result;
}
unsigned inex(unsigned *arr, unsigned len, unsigned bound) {
unsigned i, result = bound, t;
for(i = 0; i < len; ++i) {
result -= recur(arr, len, i, 1, bound);
}
return result;
}
call it with
unsigned S[N] = {...};
inex(S, N, L-1);
You need not add the 1 for the 0 anywhere, since 0 is divisible by all numbers, compute the count of numbers 1 <= k < L which are not divisible by any s_i.
Create an array of flags with L entries. Then mark each touched leaf:
for(each size in list of sizes) {
length = 0;
while(length < L) {
array[length] = TOUCHED;
length += size;
}
}
Then find the untouched leaves:
for(length = 0; length < L; length++) {
if(array[length] != TOUCHED) { /* Untouched leaf! */ }
}
Note that there is no multiplication and no division involved; but you will need up to about 1 GiB of RAM. If RAM is a problem the you can use an array of bits (max. 120 MiB).
This is only a beginning though, as there are repeating patterns that can be copied instead of generated. The first pattern is from 0 to S1*S2, the next is from 0 to S1*S2*S3, the next is from 0 to S1*S2*S3*S4, etc.
Basically, you can set all values touched by S1 and then S2 from 0 to S1*S2; then copy the pattern from 0 to S1*S2 until you get to S1*S2*S3 and set all the S3's between S3 and S1*S2*S3; then copy that pattern until you get to S1*S2*S3*S4 and set all the S4's between S4 and S1*S2*S3*S4 and so on.
Next; if S1*S2*...Sn is smaller than L, you know the pattern will repeat and can generate the results for lengths from S1*S2*...Sn to L from the pattern. In this case the size of the array only needs to be S1*S2*...Sn and doesn't need to be L.
Finally, if S1*S2*...Sn is larger than L; then you could generate the pattern for S1*S2*...(Sn-1) and use that pattern to create the results from S1*S2*...(Sn-1) to S1*S2*...Sn. In this case if S1*S2*...(Sn-1) is smaller than L then the array doesn't need to be as large as L.
I'm afraid your problem understanding is maybe not correct.
You have L. You have a set S of K elements. You must count the sum of quotient of L / Si. For L = 20, K = 1, S = { 5 }, the answer is simply 16 (20 - 20 / 5). But K > 1, so you must consider the common multiples also.
Why loop through a list of subsets? It doesn't involve subset calculation, only division and multiple.
You have K distinct integers. Each number could be a prime number. You must consider common multiples. That's all.
EDIT
L = 20 and S = {3,2,5}
Leaves could be eaten by 3 = 6
Leaves could be eaten by 2 = 10
Leaves could be eaten by 5 = 4
Common multiples of S, less than L, not in S = 6, 10, 15
Actually eaten leaves = 20/3 + 20/2 + 20/5 - 20/6 - 20/10 - 20/15 = 6
You can keep track of the distance until then next touched leaf for each size. The distance to the next touched leaf will be whichever distance happens to be smallest, and you'd subtract this distance from all the others (and wrap whenever the distance is zero).
For example:
int sizes[4] = {2, 5, 7, 9};
int distances[4];
int currentLength = 0;
for(size = 0 to 3) {
distances[size] = sizes[size];
}
while(currentLength < L) {
smallest = INT_MAX;
for(size = 0 to 3) {
if(distances[size] < smallest) smallest = distances[size];
}
for(size = 0 to 3) {
distances[size] -= smallest;
if(distances[size] == 0) distances[size] = sizes[size];
}
while( (smallest > 1) && (currentLength < L) ) {
currentLength++;
printf("%d\n", currentLength;
smallest--;
}
}
#A.06: u r the one with username linkinmew on opc, rite?
Anyways, the answer just requires u to make all possible subsets, and then apply inclusion exclusion principle. This will fall well within the time bounds for the data given. For making all possible subsets, u can easily define a recursive function.
i don't know about programming but in math there is a single theorem which works on a set that has GCD 1
L=20, S=(3,2,5)
(1-1/p)(1-1/q)(1-1/r).....and so on
(1-1/3)(1-1/2)(1-1/5)=(2/3)(1/2)(4/5)=4/15
4/15 means there are 4 numbers in each set of 15 number which are not divisible by any number rest of it can be count manually eg.
16, 17, 18, 19, 20 (only 17 and 19 means there are only 2 numbers thatr can't be divided by any S)
4+2=6
6/20 means there are only 6 numbers in first 20 numbers that can't be divided by any s

Find the largest prime number factor?

I need to find
The prime factors of 13195 are 5, 7, 13 and 29.
/ * Largest is 377. * /
What is the largest prime factor of the number 600851475143 ?
#include<stdio.h>
int main()
{
int i, j = 0;
/*Code works really fine for 13195 or 26*/
long value, large = 600851475143 /*13195*/;
for(value = (large - 1) ; value >= 3; value--)
{
if(large % value == 0)
{
/*printf("I am here \n");*/
if((value % 2 != 0) && (value % 3 != 0) && (value % 5 != 0) && (value % 7 != 0) )
{
j = 1;
break;
}
}
}
if (j == 1)
{
printf("%ld", value);
}
return 0;
}
Where it is going wrong?
600851475143 is too big to fit in 32 bit integer. long may be 32 bit on your machine. You need to use 64 bit type. The exact data type will be dependent on your platform, compiler.
Your prime checking code is wrong. You are assuming that if something is not devided by 2, 3, 5, 7 then that is prime.
The most important thing that is wrong here is that your code is too slow: even if you fix other issues, such as using a wrong data type for your integers and trying out some divisors that are definitely not prime, iterating by one down from 10^11 will simply not finish in your computer's lifetime is extremely wasteful.
I highly recommend that you read through the example on page 35 of this classic book, where Dijkstra takes you through the process of writing a program printing the first 1000 prime numbers. This example should provide enough mathematical intuition to you to speed up your own calculations, including the part where you start your search from the square root of the number that you are trying to factor.
600851475143 is probably above the precision of your platform's long data type. It requires at least 40 bits to store. You can use this to figure out how many bits you have:
#include <limits.h>
printf("my compiler uses %u bits for the long data type\n", (unsigned int) (CHAR_BIT * sizeof (long)));
#include<stdio.h>
//Euler problem #3
int main(){
long long i, sqi;
long long value, large = 600851475143LL;
long long max = 0LL;
i = 2LL;
sqi = 4LL; //i*i
for(value = large; sqi <= value ; sqi += 2LL * i++ + 1LL){
while(value % i == 0LL){
value /= (max=i);
}
}
if(value != 1LL && value != large){
max = value;
}
if(max == 0LL){
max = large;
}
printf("%lld\n", max);
return 0;
}
You need to add an L as suffix to a number that overflow MAX INT, so this line:
long value, large = 600851475143;
Should be:
long value, large = 600851475143L;
// ^
In order to do this you need to establish that the value is prime - i.e. that is has no prime factors.
Now your little piece of code checking 3/5/7 simply isn't good enough - you need to check is value has ANY lower prime factors (for example 11/13/17).
From a strategic perspective if you want to use this analysis you need to check a list of every prime factor you have found so far and check against them as you are checking against the first 3 primes.
An easier (but less efficient) method would be to write an IsPrimeFunction() and check the primality of the each divisor and store the largest.
public class LargeFactor{
public static void main(String []args){
long num = 600851475143L;
long largestFact = 0;
long[] factors = new long[2];
for (long i = 2; i * i < num; i++) {
if (num % i == 0) { // It is a divisor
factors[0] = i;
factors[1] = num / i;
for (int k = 0; k < 2; k++) {
boolean isPrime = true;
for (long j = 2; j * j < factors[k]; j++) {
if (factors[k] % j == 0) {
isPrime = false;
break;
}
}
if (isPrime && factors[k] > largestFact) {
largestFact = factors[k];
}
}
}
}
System.out.println(largestFact);
}
}
Above code utilises the fact that we only need to check all numbers up to the square root when looking for factors.

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