问题
I was wondering if someone here have a good implementation of the Sieve of Atkin that they would like to share.
I am trying to implement it, but can't quite wrap my head around it. Here is what I have so far.
public class Atkin : IEnumerable<ulong>
{
private readonly List<ulong> primes;
private readonly ulong limit;
public Atkin(ulong limit)
{
this.limit = limit;
primes = new List<ulong>();
}
private void FindPrimes()
{
var isPrime = new bool[limit + 1];
var sqrt = Math.Sqrt(limit);
for (ulong x = 1; x <= sqrt; x++)
for (ulong y = 1; y <= sqrt; y++)
{
var n = 4*x*x + y*y;
if (n <= limit && (n % 12 == 1 || n % 12 == 5))
isPrime[n] ^= true;
n = 3*x*x + y*y;
if (n <= limit && n % 12 == 7)
isPrime[n] ^= true;
n = 3*x*x - y*y;
if (x > y && n <= limit && n % 12 == 11)
isPrime[n] ^= true;
}
for (ulong n = 5; n <= sqrt; n++)
if (isPrime[n])
for (ulong k = n*n; k <= limit; k *= k)
isPrime[k] = false;
primes.Add(2);
primes.Add(3);
for (ulong n = 5; n <= limit; n++)
if (isPrime[n])
primes.Add(n);
}
public IEnumerator<ulong> GetEnumerator()
{
if (!primes.Any())
FindPrimes();
foreach (var p in primes)
yield return p;
}
IEnumerator IEnumerable.GetEnumerator()
{
return GetEnumerator();
}
}
I have pretty much just tried to "translate" the pseudocode listed at Wikipedia, but it isn't working correctly. So either I have misunderstood something or just done something wrong. Or most likely both...
Have a list of the first 500 primes which I use as a test and my implementation fails at number 40(or 41?).
Values differ at index [40]
Expected: 179
But was: 175
Are you able to find my mistake, do you have an implementation laying around that you could share, or both?
The exact test I am using looks like this:
public abstract class AtkinTests
{
[Test]
public void GetEnumerator_FirstFiveHundredNumbers_AreCorrect()
{
var sequence = new Atkin(2000000);
var actual = sequence.Take(500).ToArray();
var expected = First500;
CollectionAssert.AreEqual(expected, actual);
}
private static readonly ulong[] First500 = new ulong[]
{
2, 3, 5, 7, 11, 13, 17, ...
};
}
回答1:
This code:
for (ulong k = n*n; k <= limit; k *= k)
isPrime[k] = false;
doesn't seem to be a faithful translation of this pseudocode:
is_prime(k) ← false, k ∈ {n², 2n², 3n², ..., limit}
Your code looks like it will run for n * n, n ^ 4, n ^ 8, etc. i.e. squaring each time instead of adding n-squared each time. Try this:
ulong nSquared = n * n;
for (ulong k = nSquared; k <= limit; k += nSquared)
isPrime[k] = false;
回答2:
The last answer by Aaron Mugatroyd as from the translated Python source for a Sieve of Atkin (SoA) isn't too bad, but it can be improved in several respects as it misses some important optimizations, as follows:
His answer doesn't use the full modulo 60 original Atkin and Bernstein version of the Sieve but rather a slightly improved variation of the pseudo code from the Wikipedia article so uses about a factor of 0.36 of the numerical sieve range combined toggle/cull operations; my code below uses the reasonably efficient non-page segment pseudo code as per my comments in an answer commenting on the Sieve of Atkin which uses a factor of about 0.26 times the numerical range to reduce the amount of work done to about a factor of about two sevenths.
His code reduces the buffer size by only having odd number representations, whereas my code further bit packs to eliminate any representation of the numbers divisible by three and five as well as those divisible by two implied by "odds-only"; this reduces the memory requirement by a further factor of almost half (to 8/15) and helps make better use of the CPU caches for a further increase in speed due to reduced average memory access time.
My code counts the number of primes using a fast Look Up Table (LUT) pop count technique to take almost no time to count as compared to the approximately one second using the bit-by-bit technique he uses; however, in this sample code even that small time is taken out of the timed portion of the code.
Finally, my code optimizes the bit manipulation operations for a minimum of code per inner loop. For instance, it does not use continual right shift by one to produce the odd representation index and in fact little bit shifting at all by writing all of the inner loops as constant modulo (equals bit position) operations. As well, Aaron's translated code is quite inefficient in operations as for instance in prime square free culling it adds the square of the prime to the index then checks for an odd result rather than just adding two times the square so as not to require the check; then it makes even the check redundant by shifting the number right by one (dividing by two) before doing the cull operation in the inner loop, just as it does for all the loops. This inefficient code won't make much of a difference in execution time for large ranges using this "large sieve buffer array" technique, as most of the time per operation is used in RAM memory access (about 37 CPU clock cycles or more for a range of one billion), but will make the execution time much slower than it needs to be for smaller ranges which fit into the CPU caches; in other words it sets a too high lowest limit in execution speed per operation.
The code is as follows:
//Sieve of Atkin based on full non page segmented modulo 60 implementation...
using System;
using System.Collections;
using System.Collections.Generic;
using System.Linq;
namespace NonPagedSoA {
//implements the non-paged Sieve of Atkin (full modulo 60 version)...
class SoA : IEnumerable<ulong> {
private ushort[] buf = null;
private long cnt = 0;
private long opcnt = 0;
private static byte[] modPRMS = { 7, 11, 13, 17, 19, 23, 29, 31, 37, 41, 43, 47, 49, 53, 59, 61 };
private static ushort[] modLUT;
private static byte[] cntLUT;
//initialize the private LUT's...
static SoA() {
modLUT = new ushort[60];
for (int i = 0, m = 0; i < modLUT.Length; ++i) {
if ((i & 1) != 0 || (i + 7) % 3 == 0 || (i + 7) % 5 == 0) modLUT[i] = 0;
else modLUT[i] = (ushort)(1 << (m++));
}
cntLUT = new byte[65536];
for (int i = 0; i < cntLUT.Length; ++i) {
var c = 0;
for (int j = i; j > 0; j >>= 1) c += j & 1;
cntLUT[i] = (byte)c;
}
}
//initialization and all the work producing the prime bit array done in the constructor...
public SoA(ulong range) {
this.opcnt = 0;
if (range < 7) {
if (range > 1) {
cnt = 1;
if (range > 2) this.cnt += (long)(range - 1) / 2;
}
this.buf = new ushort[0];
}
else {
this.cnt = 3;
var nrng = range - 7; var lmtw = nrng / 60;
//initialize sufficient wheels to non-prime
this.buf = new ushort[lmtw + 1];
//Put in candidate primes:
//for the 4 * x ^ 2 + y ^ 2 quadratic solution toggles - all x odd y...
ulong n = 6; // equivalent to 13 - 7 = 6...
for (uint x = 1, y = 3; n <= nrng; n += (x << 3) + 4, ++x, y = 1) {
var cb = n; if (x <= 1) n -= 8; //cancel the effect of skipping the first one...
for (uint i = 0; i < 15 && cb <= range; cb += (y << 2) + 4, y += 2, ++i) {
var cbd = cb / 60; var cm = modLUT[cb % 60];
if (cm != 0)
for (uint c = (uint)cbd, my = y + 15; c < buf.Length; c += my, my += 30) {
buf[c] ^= cm; // ++this.opcnt;
}
}
}
//for the 3 * x ^ 2 + y ^ 2 quadratic solution toggles - x odd y even...
n = 0; // equivalent to 7 - 7 = 0...
for (uint x = 1, y = 2; n <= nrng; n += ((x + x + x) << 2) + 12, x += 2, y = 2) {
var cb = n;
for (var i = 0; i < 15 && cb <= range; cb += (y << 2) + 4, y += 2, ++i) {
var cbd = cb / 60; var cm = modLUT[cb % 60];
if (cm != 0)
for (uint c = (uint)cbd, my = y + 15; c < buf.Length; c += my, my += 30) {
buf[c] ^= cm; // ++this.opcnt;
}
}
}
//for the 3 * x ^ 2 - y ^ 2 quadratic solution toggles all x and opposite y = x - 1...
n = 4; // equivalent to 11 - 7 = 4...
for (uint x = 2, y = x - 1; n <= nrng; n += (ulong)(x << 2) + 4, y = x, ++x) {
var cb = n; int i = 0;
for ( ; y > 1 && i < 15 && cb <= nrng; cb += (ulong)(y << 2) - 4, y -= 2, ++i) {
var cbd = cb / 60; var cm = modLUT[cb % 60];
if (cm != 0) {
uint c = (uint)cbd, my = y;
for ( ; my >= 30 && c < buf.Length; c += my - 15, my -= 30) {
buf[c] ^= cm; // ++this.opcnt;
}
if (my > 0 && c < buf.Length) { buf[c] ^= cm; /* ++this.opcnt; */ }
}
}
if (y == 1 && i < 15) {
var cbd = cb / 60; var cm = modLUT[cb % 60];
if ((cm & 0x4822) != 0 && cbd < (ulong)buf.Length) { buf[cbd] ^= cm; /* ++this.opcnt; */ }
}
}
//Eliminate squares of base primes, only for those on the wheel:
for (uint i = 0, w = 0, pd = 0, pn = 0, msk = 1; w < this.buf.Length ; ++i) {
uint p = pd + modPRMS[pn];
ulong sqr = (ulong)p * (ulong)p; //to handle ranges above UInt32.MaxValue
if (sqr > range) break;
if ((this.buf[w] & msk) != 0) { //found base prime, square free it...
ulong s = sqr - 7;
for (int j = 0; s <= nrng && j < modPRMS.Length; s = sqr * modPRMS[j] - 7, ++j) {
var cd = s / 60; var cm = (ushort)(modLUT[s % 60] ^ 0xFFFF);
//may need ulong loop index for ranges larger than two billion
//but buf length only good to about 2^31 * 60 = 120 million anyway,
//even with large array setting and half that with 32-bit...
for (ulong c = cd; c < (ulong)this.buf.Length; c += sqr) {
this.buf[c] &= cm; // ++this.opcnt;
}
}
}
if (msk >= 0x8000) { msk = 1; pn = 0; ++w; pd += 60; }
else { msk <<= 1; ++pn; }
}
//clear any overflow primes in the excess space in the last wheel/word:
var ndx = nrng % 60; //clear any primes beyond the range
for (; modLUT[ndx] == 0; --ndx) ;
this.buf[lmtw] &= (ushort)((modLUT[ndx] << 1) - 1);
}
}
//uses a fast pop count Look Up Table to return the total number of primes...
public long Count {
get {
long cnt = this.cnt;
for (int i = 0; i < this.buf.Length; ++i) cnt += cntLUT[this.buf[i]];
return cnt;
}
}
//returns the number of toggle/cull operations used to sieve the prime bit array...
public long Ops {
get {
return this.opcnt;
}
}
//generate the enumeration of primes...
public IEnumerator<ulong> GetEnumerator() {
yield return 2; yield return 3; yield return 5;
ulong pd = 0;
for (uint i = 0, w = 0, pn = 0, msk = 1; w < this.buf.Length; ++i) {
if ((this.buf[w] & msk) != 0) //found a prime bit...
yield return pd + modPRMS[pn]; //add it to the list
if (msk >= 0x8000) { msk = 1; pn = 0; ++w; pd += 60; }
else { msk <<= 1; ++pn; }
}
}
//required for the above enumeration...
IEnumerator IEnumerable.GetEnumerator() {
return this.GetEnumerator();
}
}
class Program {
static void Main(string[] args) {
Console.WriteLine("This program calculates primes by a simple full version of the Sieve of Atkin.\r\n");
const ulong n = 1000000000;
var elpsd = -DateTime.Now.Ticks;
var gen = new SoA(n);
elpsd += DateTime.Now.Ticks;
Console.WriteLine("{0} primes found to {1} using {2} operations in {3} milliseconds.", gen.Count, n, gen.Ops, elpsd / 10000);
//Output prime list for testing...
//Console.WriteLine();
//foreach (var p in gen) {
// Console.Write(p + " ");
//}
//Console.WriteLine();
//Test options showing what one can do with the enumeration, although more slowly...
// Console.WriteLine("\r\nThere are {0} primes with the last one {1} and the sum {2}.",gen.Count(),gen.Last(),gen.Sum(x => (long)x));
Console.Write("\r\nPress any key to exit:");
Console.ReadKey(true);
Console.WriteLine();
}
}
}
This code runs about twice as fast as Aaron's code (about 2.7 seconds using 64-bit or 32-bit mode on an i7-2700K (3.5 GHz) with the buffer about 16.5 Megabytes and about 0.258 billion combined toggle/prime square free cull operations (which can be shown by uncommenting the "++this.opcnt" statements) for a sieve range of one billion, as compared to 5.4/6.2 seconds (32-bit/64-bit) for his code without the count time and almost twice the memory use using about 0.359 billion combined toggle/cull operations for sieving up to one billion.
Although it is faster than his most optimized naive odds-only implementation of the non-paged Sieve of Eratosthenes (SoE), that does not make the Sieve of Atkin faster than the Sieve of Eratosthenes, as if one applies similar techniques as used in the above SoA implementation to the SoE plus uses maximal wheel factorization, the SoE will about the same speed as this.
Analysis: Although the number of operations for the fully optimized SoE are about the same as the number of operations for the SoA for a sieve range of one billion, the main bottleneck for these non-paged implementations is memory access once the sieve buffer size exceeds the CPU cache sizes (32 KiloBytes L1 cache at one clock cycle access, 256 Kilobytes L2 cache at about four clock cycles access time and 8 Megabytes L3 cache at about 20 clock cycles access time for my i7), after which memory access can exceed a hundred clock cycles.
Now both have a factor of about eight improvement in memory access speeds when one adapts the algorithms to page segmentation so one can sieve ranges that would not otherwise fit into available memory. However, the SoE continues to gain over the SoA as the sieve range starts to get very large due to difficulties in implementing the "primes square free" part of the algorithm due to the huge strides in culling scans that quickly grow to many hundreds of times the size of the page buffers. As well, and perhaps more serious, it gets very memory and/or computationally intensive to compute the new start point for each value of 'x' as to the value of 'y' at the lowest representation of each page buffer for a further quite large loss in efficiency of the paged SoA comparaed to the SoE as the range grows.
EDIT_ADD: The odds-only SoE as used by Aaron Murgatroyd uses about 1.026 billion cull operations for a sieve range of one billion so about four times as many operations as the SoA and thus should run about four times slower, but the SoA even as implemented here has a more complex inner loop and especially due to a much higher proportion of the odds-only SoE culls have a much shorter stride in the culling scans than the strides of the SoA the naive odds-only SoE has much better average memory access times in spite of the sieve buffer greatly exceeding the CPU cache sizes (better use of cache associativity). This explains why the above SoA is only about twice as fast as the odds-only SoE even though it would theoretically seem to be doing only one quarter of the work.
If one were to use a similar algorithm using constant modulo inner loops as for the above SoA and implemented the same 2/3/5 wheel factorization, the SoE would reduce the number of cull operations to about 0.405 billion operations so only about 50% more operations than the SoA and would theoretically run just slightly slower than the SoA, but may run at about the same speed due to the cull strides still being a little smaller than for the SoA on the average for this "naive" large memory buffer use. Increasing the wheel factorization to the 2/3/5/7 wheel means the SoE cull operations are reduced to about 0.314 for a cull range of one billion and may make that version of the SoE run about the same speed for this algorithm.
Further use of wheel factorization can be made by pre-culling the sieve array (copying in a pattern) for the 2/3/5/7/11/13/17/19 prime factors at almost no cost in execution time to reduce the total number of cull operations to about 0.251 billion for a sieve range of one billion and the SoE will run faster or about the same speed than even this optimized version of the SoA, even for these large memory buffer versions, with the SoE still having much less code complexity than the above.
Thus, it can be seen that the number of operations for the SoE can be greatly reduced from a naive or even odds-only or 2/3/5 wheel factorization version such that the number of operations are about the same as for the SoA while at the same time the time per operation may actually be less due to both less complex inner loops and more efficient memory access. END_EDIT_ADD
EDIT_ADD2: I here add the code for a SoE using a similiar constant modulo/bit position technique for the innermost loops as for the SoA above according to the pseudo code further down the answer as linked above. The code is quite a bit less complex than the above SoA in spite of having high wheel factorization and pre-culling applied such that the total number of cull operations are actually less than the combined toggle/cull operations for the SoA up to a sieving rang of about two billion. The code as follows:
EDIT_FINAL Corrected code below and comments related to it END_EDIT_FINAL
//Sieve of Eratosthenes based on maximum wheel factorization and pre-culling implementation...
using System;
using System.Collections;
using System.Collections.Generic;
namespace NonPagedSoE {
//implements the non-paged Sieve of Eratosthenes (full modulo 210 version with preculling)...
class SoE : IEnumerable<ulong> {
private ushort[] buf = null;
private long cnt = 0;
private long opcnt = 0;
private static byte[] basePRMS = { 2, 3, 5, 7, 11, 13, 17, 19 };
private static byte[] modPRMS = { 23, 29, 31, 37, 41, 43, 47, 53, 59, 61, 67, 71, 73, 79, 83, 89, //positions + 23
97, 101, 103, 107, 109, 113, 121, 127, 131, 137, 139, 143, 149, 151, 157, 163,
167, 169, 173, 179, 181 ,187 ,191 ,193, 197, 199, 209, 211, 221, 223, 227, 229 };
private static byte[] gapsPRMS = { 6, 2, 6, 4, 2, 4, 6, 6, 2, 6, 4, 2, 6, 4, 6, 8,
4, 2, 4, 2, 4, 8, 6, 4, 6, 2, 4, 6, 2, 6, 6, 4,
2, 4, 6, 2, 6, 4, 2, 4, 2, 10, 2, 10, 2, 4, 2, 4 };
private static ulong[] modLUT;
private static byte[] cntLUT;
//initialize the private LUT's...
static SoE() {
modLUT = new ulong[210];
for (int i = 0, m = 0; i < modLUT.Length; ++i) {
if ((i & 1) != 0 || (i + 23) % 3 == 0 || (i + 23) % 5 == 0 || (i + 23) % 7 == 0) modLUT[i] = 0;
else modLUT[i] = 1UL << (m++);
}
cntLUT = new byte[65536];
for (int i = 0; i < cntLUT.Length; ++i) {
var c = 0;
for (int j = i ^ 0xFFFF; j > 0; j >>= 1) c += j & 1; //reverse logic; 0 is prime; 1 is composite
cntLUT[i] = (byte)c;
}
}
//initialization and all the work producing the prime bit array done in the constructor...
public SoE(ulong range) {
this.opcnt = 0;
if (range < 23) {
if (range > 1) {
for (int i = 0; i < modPRMS.Length; ++i) if (modPRMS[i] <= range) this.cnt++; else break;
}
this.buf = new ushort[0];
}
else {
this.cnt = 8;
var nrng = range - 23; var lmtw = nrng / 210; var lmtwt3 = lmtw * 3;
//initialize sufficient wheels to prime
this.buf = new ushort[lmtwt3 + 3]; //initial state of all zero's is all potential prime.
//initialize array to account for preculling the primes of 11, 13, 17, and 19;
//(2, 3, 5, and 7 already eliminated by the bit packing to residues).
for (int pn = modPRMS.Length - 4; pn < modPRMS.Length; ++pn) {
uint p = modPRMS[pn] - 210u; ulong pt3 = p * 3;
ulong s = p * p - 23;
ulong xrng = Math.Min(9699709, nrng); // only do for the repeating master pattern size
ulong nwrds = (ulong)Math.Min(138567, this.buf.Length);
for (int j = 0; s <= xrng && j < modPRMS.Length; s += p * gapsPRMS[(pn + j++) % 48]) {
var sm = modLUT[s % 210];
var si = (sm < (1UL << 16)) ? 0UL : ((sm < (1UL << 32)) ? 1UL : 2UL);
var cd = s / 210 * 3 + si; var cm = (ushort)(sm >> (int)(si << 4));
for (ulong c = cd; c < nwrds; c += pt3) { //tight culling loop for size of master pattern
this.buf[c] |= cm; // ++this.opcnt; //reverse logic; mark composites with ones.
}
}
}
//Now copy the master pattern so it repeats across the main buffer, allow for overflow...
for (long i = 138567; i < this.buf.Length; i += 138567)
if (i + 138567 <= this.buf.Length)
Array.Copy(this.buf, 0, this.buf, i, 138567);
else Array.Copy(this.buf, 0, this.buf, i, this.buf.Length - i);
//Eliminate all composites which are factors of base primes, only for those on the wheel:
for (uint i = 0, w = 0, wi = 0, pd = 0, pn = 0, msk = 1; w < this.buf.Length; ++i) {
uint p = pd + modPRMS[pn];
ulong sqr = (ulong)p * (ulong)p;
if (sqr > range) break;
if ((this.buf[w] & msk) == 0) { //found base prime, mark its composites...
ulong s = sqr - 23; ulong pt3 = p * 3;
for (int j = 0; s <= nrng && j < modPRMS.Length; s += p * gapsPRMS[(pn + j++) % 48]) {
var sm = modLUT[s % 210];
var si = (sm < (1UL << 16)) ? 0UL : ((sm < (1UL << 32)) ? 1UL : 2UL);
var cd = s / 210 * 3 + si; var cm = (ushort)(sm >> (int)(si << 4));
for (ulong c = cd; c < (ulong)this.buf.Length; c += pt3) { //tight culling loop
this.buf[c] |= cm; // ++this.opcnt; //reverse logic; mark composites with ones.
}
}
}
++pn;
if (msk >= 0x8000) { msk = 1; ++w; ++wi; if (wi == 3) { wi = 0; pn = 0; pd += 210; } }
else msk <<= 1;
}
//clear any overflow primes in the excess space in the last wheel/word:
var ndx = nrng % 210; //clear any primes beyond the range
for (; modLUT[ndx] == 0; --ndx) ;
var cmsk = (~(modLUT[ndx] - 1)) << 1; //force all bits above to be composite ones.
this.buf[lmtwt3++] |= (ushort)cmsk;
this.buf[lmtwt3++] |= (ushort)(cmsk >> 16);
this.buf[lmtwt3] |= (ushort)(cmsk >> 32);
}
}
//uses a fast pop count Look Up Table to return the total number of primes...
public long Count {
get {
long cnt = this.cnt;
for (int i = 0; i < this.buf.Length; ++i) cnt += cntLUT[this.buf[i]];
return cnt;
}
}
//returns the number of cull operations used to sieve the prime bit array...
public long Ops {
get {
return this.opcnt;
}
}
//generate the enumeration of primes...
public IEnumerator<ulong> GetEnumerator() {
yield return 2; yield return 3; yield return 5; yield return 7;
yield return 11; yield return 13; yield return 17; yield return 19;
ulong pd = 0;
for (uint i = 0, w = 0, wi = 0, pn = 0, msk = 1; w < this.buf.Length; ++i) {
if ((this.buf[w] & msk) == 0) //found a prime bit...
yield return pd + modPRMS[pn];
++pn;
if (msk >= 0x8000) { msk = 1; ++w; ++wi; if (wi == 3) { wi = 0; pn = 0; pd += 210; } }
else msk <<= 1;
}
}
//required for the above enumeration...
IEnumerator IEnumerable.GetEnumerator() {
return this.GetEnumerator();
}
}
class Program {
static void Main(string[] args) {
Console.WriteLine("This program calculates primes by a simple maximually wheel factorized version of the Sieve of Eratosthenes.\r\n");
const ulong n = 1000000000;
var elpsd = -DateTime.Now.Ticks;
var gen = new SoE(n);
elpsd += DateTime.Now.Ticks;
Console.WriteLine("{0} primes found to {1} using {2} operations in {3} milliseconds.", gen.Count, n, gen.Ops, elpsd / 10000);
// Console.WriteLine();
// foreach (var p in gen) {
// Console.Write(p + " ");
// }
// Console.WriteLine();
// Console.WriteLine("\r\nThere are {0} primes with the last one {1} and the sum {2}.",gen.Count(),gen.Last(),gen.Sum(x => (long)x));
Console.Write("\r\nPress any key to exit:");
Console.ReadKey(true);
Console.WriteLine();
}
}
}
This code actually runs a few percent faster than the above SoA as it should as there are slightly less operations and the main bottleneck for this large array size for a range of a billion is memory access time of something like 40 to over 100 CPU clock cycles depending on CPU and memory specifications; this means that code optimizations (other than reducing the total number of operations) are ineffective as most of the time is spend waiting on memory access. At any rate, using a huge memory buffer isn't the most efficient way to sieve large ranges, with a factor of up to about eight times improvement for the SoE using page segmentation with the same maximum wheel factorization (which also paves the way for multi-processing).
It is in implementing page segmentation and multi-processing that the SoA is really deficient for ranges much above four billion as compared to the SoE as any gains due to the reduced asymptotic complexity of the SoA rapidly get eaten up by page processing overhead factors related to the prime square free processing and calculating the much larger number of page start addresses; alternatively, one overcomes this by storing markers in RAM memory at a huge cost in memory consumption and further inefficiencies in accessing these marker store structures. END_EDIT_ADD2
In short, the SoA isn't really a practical sieve as compared to the the fully wheel factorized SoE since just as the gain in asymptotic complexity starts to bring it close in performance to the fully optimized SoE, it starts to lose efficiency due to the details of practical implementation as to relative memory access time and page segmentation complexities as well as generally being more complex and difficult to write. In my opinion it is more of an interesting intellectual concept and mental exercise than a practical sieve as compared to the SoE.
Some day I will adapt these techniques to a multi-threaded page segmented Sieve of Eratosthenes to be about as fast in C# as Atkin and Bernstein's "primegen" implementation of the SoA in 'C' and will blow it out of the water for large ranges above about four billion even single threaded, with an extra boost in speed of up to about four when multi-threading on my i7 (eight cores including Hyper Threading).
回答3:
Here's another implementation. It uses BitArray to save memory. The Parallel.For needs .NET Framework 4.
static List<int> FindPrimesBySieveOfAtkins(int max)
{
// var isPrime = new BitArray((int)max+1, false);
// Can't use BitArray because of threading issues.
var isPrime = new bool[max + 1];
var sqrt = (int)Math.Sqrt(max);
Parallel.For(1, sqrt, x =>
{
var xx = x * x;
for (int y = 1; y <= sqrt; y++)
{
var yy = y * y;
var n = 4 * xx + yy;
if (n <= max && (n % 12 == 1 || n % 12 == 5))
isPrime[n] ^= true;
n = 3 * xx + yy;
if (n <= max && n % 12 == 7)
isPrime[n] ^= true;
n = 3 * xx - yy;
if (x > y && n <= max && n % 12 == 11)
isPrime[n] ^= true;
}
});
var primes = new List<int>() { 2, 3 };
for (int n = 5; n <= sqrt; n++)
{
if (isPrime[n])
{
primes.Add(n);
int nn = n * n;
for (int k = nn; k <= max; k += nn)
isPrime[k] = false;
}
}
for (int n = sqrt + 1; n <= max; n++)
if (isPrime[n])
primes.Add(n);
return primes;
}
回答4:
Here is a faster implementation of the Sieve of Atkin, I stole the algorithm from this Python script here (I take no credit for the algorithm):
http://programmingpraxis.com/2010/02/19/sieve-of-atkin-improved/
using System;
using System.Collections;
using System.Collections.Generic;
namespace PrimeGenerator
{
// The block element type for the bit array,
// use any unsigned value. WARNING: UInt64 is
// slower even on x64 architectures.
using BitArrayType = System.UInt32;
// This should never be any bigger than 256 bits - leave as is.
using BitsPerBlockType = System.Byte;
// The prime data type, this can be any unsigned value, the limit
// of this type determines the limit of Prime value that can be
// found. WARNING: UInt64 is slower even on x64 architectures.
using PrimeType = System.Int32;
/// <summary>
/// Calculates prime number using the Sieve of Eratosthenes method.
/// </summary>
/// <example>
/// <code>
/// var lpPrimes = new Eratosthenes(1e7);
/// foreach (UInt32 luiPrime in lpPrimes)
/// Console.WriteLine(luiPrime);
/// </example>
public class Atkin : IEnumerable<PrimeType>
{
#region Constants
/// <summary>
/// Constant for number of bits per block, calculated based on size of BitArrayType.
/// </summary>
const BitsPerBlockType cbBitsPerBlock = sizeof(BitArrayType) * 8;
#endregion
#region Protected Locals
/// <summary>
/// The limit for the maximum prime value to find.
/// </summary>
protected readonly PrimeType mpLimit;
/// <summary>
/// The number of primes calculated or null if not calculated yet.
/// </summary>
protected PrimeType? mpCount = null;
/// <summary>
/// The current bit array where a set bit means
/// the odd value at that location has been determined
/// to not be prime.
/// </summary>
protected BitArrayType[] mbaOddPrime;
#endregion
#region Initialisation
/// <summary>
/// Create Sieve of Atkin generator.
/// </summary>
/// <param name="limit">The limit for the maximum prime value to find.</param>
public Atkin(PrimeType limit)
{
// Check limit range
if (limit > PrimeType.MaxValue - (PrimeType)Math.Sqrt(PrimeType.MaxValue))
throw new ArgumentOutOfRangeException();
mpLimit = limit;
FindPrimes();
}
#endregion
#region Private Methods
/// <summary>
/// Finds the prime number within range.
/// </summary>
private unsafe void FindPrimes()
{
// Allocate bit array.
mbaOddPrime = new BitArrayType[(((mpLimit >> 1) + 1) / cbBitsPerBlock) + 1];
PrimeType lpYLimit, lpN, lpXX3, lpXX4, lpDXX, lpDN, lpDXX4, lpXX, lpX, lpYY, lpMinY, lpS, lpK;
fixed (BitArrayType* lpbOddPrime = &mbaOddPrime[0])
{
// n = 3x^2 + y^2 section
lpXX3 = 3;
for (lpDXX = 0; lpDXX < 12 * SQRT((mpLimit - 1) / 3); lpDXX += 24)
{
lpXX3 += lpDXX;
lpYLimit = (12 * SQRT(mpLimit - lpXX3)) - 36;
lpN = lpXX3 + 16;
for (lpDN = -12; lpDN < lpYLimit + 1; lpDN += 72)
{
lpN += lpDN;
lpbOddPrime[(lpN >> 1) / cbBitsPerBlock] ^=
(BitArrayType)((BitArrayType)1 << (int)((lpN >> 1) % cbBitsPerBlock));
}
lpN = lpXX3 + 4;
for (lpDN = 12; lpDN < lpYLimit + 1; lpDN += 72)
{
lpN += lpDN;
lpbOddPrime[(lpN >> 1) / cbBitsPerBlock] ^=
(BitArrayType)((BitArrayType)1 << (int)((lpN >> 1) % cbBitsPerBlock));
}
}
// # n = 4x^2 + y^2 section
lpXX4 = 0;
for (lpDXX4 = 4; lpDXX4 < 8 * SQRT((mpLimit - 1) / 4) + 4; lpDXX4 += 8)
{
lpXX4 += lpDXX4;
lpN = lpXX4 + 1;
if ((lpXX4 % 3) != 0)
{
for (lpDN = 0; lpDN < (4 * SQRT(mpLimit - lpXX4)) - 3; lpDN += 8)
{
lpN += lpDN;
lpbOddPrime[(lpN >> 1) / cbBitsPerBlock] ^=
(BitArrayType)((BitArrayType)1 << (int)((lpN >> 1) % cbBitsPerBlock));
}
}
else
{
lpYLimit = (12 * SQRT(mpLimit - lpXX4)) - 36;
lpN = lpXX4 + 25;
for (lpDN = -24; lpDN < lpYLimit + 1; lpDN += 72)
{
lpN += lpDN;
lpbOddPrime[(lpN >> 1) / cbBitsPerBlock] ^=
(BitArrayType)((BitArrayType)1 << (int)((lpN >> 1) % cbBitsPerBlock));
}
lpN = lpXX4 + 1;
for (lpDN = 24; lpDN < lpYLimit + 1; lpDN += 72)
{
lpN += lpDN;
lpbOddPrime[(lpN >> 1) / cbBitsPerBlock] ^=
(BitArrayType)((BitArrayType)1 << (int)((lpN >> 1) % cbBitsPerBlock));
}
}
}
// # n = 3x^2 - y^2 section
lpXX = 1;
for (lpX = 3; lpX < SQRT(mpLimit / 2) + 1; lpX += 2)
{
lpXX += 4 * lpX - 4;
lpN = 3 * lpXX;
if (lpN > mpLimit)
{
lpMinY = ((SQRT(lpN - mpLimit) >> 2) << 2);
lpYY = lpMinY * lpMinY;
lpN -= lpYY;
lpS = 4 * lpMinY + 4;
}
else
lpS = 4;
for (lpDN = lpS; lpDN < 4 * lpX; lpDN += 8)
{
lpN -= lpDN;
if (lpN <= mpLimit && lpN % 12 == 11)
lpbOddPrime[(lpN >> 1) / cbBitsPerBlock] ^=
(BitArrayType)((BitArrayType)1 << (int)((lpN >> 1) % cbBitsPerBlock));
}
}
// xx = 0
lpXX = 0;
for (lpX = 2; lpX < SQRT(mpLimit / 2) + 1; lpX += 2)
{
lpXX += 4*lpX - 4;
lpN = 3*lpXX;
if (lpN > mpLimit)
{
lpMinY = ((SQRT(lpN - mpLimit) >> 2) << 2) - 1;
lpYY = lpMinY * lpMinY;
lpN -= lpYY;
lpS = 4*lpMinY + 4;
}
else
{
lpN -= 1;
lpS = 0;
}
for (lpDN = lpS; lpDN < 4 * lpX; lpDN += 8)
{
lpN -= lpDN;
if (lpN <= mpLimit && lpN % 12 == 11)
lpbOddPrime[(lpN>>1) / cbBitsPerBlock] ^=
(BitArrayType)((BitArrayType)1 << (int)((lpN>>1) % cbBitsPerBlock));
}
}
// # eliminate squares
for (lpN = 5; lpN < SQRT(mpLimit) + 1; lpN += 2)
if ((lpbOddPrime[(lpN >> 1) / cbBitsPerBlock] & ((BitArrayType)1 << (int)((lpN >> 1) % cbBitsPerBlock))) != 0)
for (lpK = lpN * lpN; lpK < mpLimit; lpK += lpN * lpN)
if ((lpK & 1) == 1)
lpbOddPrime[(lpK >> 1) / cbBitsPerBlock] &=
(BitArrayType)~((BitArrayType)1 << (int)((lpK >> 1) % cbBitsPerBlock));
}
}
/// <summary>
/// Calculates the truncated square root for a number.
/// </summary>
/// <param name="value">The value to get the square root for.</param>
/// <returns>The truncated sqrt of the value.</returns>
private unsafe PrimeType SQRT(PrimeType value)
{
return (PrimeType)Math.Sqrt(value);
}
/// <summary>
/// Gets a bit value by index.
/// </summary>
/// <param name="bits">The blocks containing the bits.</param>
/// <param name="index">The index of the bit.</param>
/// <returns>True if bit is set, false if cleared.</returns>
private bool GetBitSafe(BitArrayType[] bits, PrimeType index)
{
if ((index & 1) == 1)
return (bits[(index >> 1) / cbBitsPerBlock] & ((BitArrayType)1 << (int)((index >> 1) % cbBitsPerBlock))) != 0;
else
return false;
}
#endregion
#region Public Properties
/// <summary>
/// Get the limit for the maximum prime value to find.
/// </summary>
public PrimeType Limit
{
get
{
return mpLimit;
}
}
/// <summary>
/// Returns the number of primes found in the range.
/// </summary>
public PrimeType Count
{
get
{
if (!mpCount.HasValue)
{
PrimeType lpCount = 0;
foreach (PrimeType liPrime in this) lpCount++;
mpCount = lpCount;
}
return mpCount.Value;
}
}
/// <summary>
/// Determines if a value in range is prime or not.
/// </summary>
/// <param name="test">The value to test for primality.</param>
/// <returns>True if the value is prime, false otherwise.</returns>
public bool this[PrimeType test]
{
get
{
if (test > mpLimit) throw new ArgumentOutOfRangeException();
if (test <= 1) return false;
if (test == 2) return true;
if ((test & 1) == 0) return false;
return !GetBitSafe(mbaOddPrime, test >> 1);
}
}
#endregion
#region Public Methods
/// <summary>
/// Gets the enumerator for the primes.
/// </summary>
/// <returns>The enumerator of the primes.</returns>
public IEnumerator<PrimeType> GetEnumerator()
{
// return [2,3] + filter(primes.__getitem__, xrange(5,limit,2))
// Two & Three always prime.
yield return 2;
yield return 3;
// Start at first block, third MSB (5).
int liBlock = 0;
byte lbBit = 2;
BitArrayType lbaCurrent = mbaOddPrime[0] >> lbBit;
// For each value in range stepping in incrments of two for odd values.
for (PrimeType lpN = 5; lpN <= mpLimit; lpN += 2)
{
// If current bit not set then value is prime.
if ((lbaCurrent & 1) == 1)
yield return lpN;
// Move to NSB.
lbaCurrent >>= 1;
// Increment bit value.
lbBit++;
// If block is finished.
if (lbBit == cbBitsPerBlock)
{
lbBit = 0;
lbaCurrent = mbaOddPrime[++liBlock];
//// Move to first bit of next block skipping full blocks.
while (lbaCurrent == 0)
{
lpN += ((PrimeType)cbBitsPerBlock) << 1;
if (lpN <= mpLimit)
lbaCurrent = mbaOddPrime[++liBlock];
else
break;
}
}
}
}
#endregion
#region IEnumerable<PrimeType> Implementation
/// <summary>
/// Gets the enumerator for the primes.
/// </summary>
/// <returns></returns>
IEnumerator IEnumerable.GetEnumerator()
{
return GetEnumerator();
}
#endregion
}
}
Its close in speed to my most optimised version of the Sieve of Eratosthenes, but its still slower by about 20%, it can be found here:
https://stackoverflow.com/a/9700790/738380
回答5:
Heres mine, it uses a class called CompartmentalisedParallel which allows you to perform parallel for loops but control the number of threads so that the indexes are grouped up. However, due to the threading issues you need to either lock the BitArray each time it is altered or create a separate BitArray for each thread and then XOR them together at the end, the first option was pretty slow because the amount of locks, the second option seemed faster for me!
using System;
using System.Collections;
using System.Collections.Generic;
using System.Threading.Tasks;
namespace PrimeGenerator
{
public class Atkin : Primes
{
protected BitArray mbaPrimes;
protected bool mbThreaded = true;
public Atkin(int limit)
: this(limit, true)
{
}
public Atkin(int limit, bool threaded)
: base(limit)
{
mbThreaded = threaded;
if (mbaPrimes == null) FindPrimes();
}
public bool Threaded
{
get
{
return mbThreaded;
}
}
public override IEnumerator<int> GetEnumerator()
{
yield return 2;
yield return 3;
for (int lsN = 5; lsN <= msLimit; lsN += 2)
if (mbaPrimes[lsN]) yield return lsN;
}
private void FindPrimes()
{
mbaPrimes = new BitArray(msLimit + 1, false);
int lsSQRT = (int)Math.Sqrt(msLimit);
int[] lsSquares = new int[lsSQRT + 1];
for (int lsN = 0; lsN <= lsSQRT; lsN++)
lsSquares[lsN] = lsN * lsN;
if (Threaded)
{
CompartmentalisedParallel.For<BitArray>(
1, lsSQRT + 1, new ParallelOptions(),
(start, finish) => { return new BitArray(msLimit + 1, false); },
(lsX, lsState, lbaLocal) =>
{
int lsX2 = lsSquares[lsX];
for (int lsY = 1; lsY <= lsSQRT; lsY++)
{
int lsY2 = lsSquares[lsY];
int lsN = 4 * lsX2 + lsY2;
if (lsN <= msLimit && (lsN % 12 == 1 || lsN % 12 == 5))
lbaLocal[lsN] ^= true;
lsN -= lsX2;
if (lsN <= msLimit && lsN % 12 == 7)
lbaLocal[lsN] ^= true;
if (lsX > lsY)
{
lsN -= lsY2 * 2;
if (lsN <= msLimit && lsN % 12 == 11)
lbaLocal[lsN] ^= true;
}
}
return lbaLocal;
},
(lbaResult, start, finish) =>
{
lock (mbaPrimes)
mbaPrimes.Xor(lbaResult);
},
-1
);
}
else
{
for (int lsX = 1; lsX <= lsSQRT; lsX++)
{
int lsX2 = lsSquares[lsX];
for (int lsY = 1; lsY <= lsSQRT; lsY++)
{
int lsY2 = lsSquares[lsY];
int lsN = 4 * lsX2 + lsY2;
if (lsN <= msLimit && (lsN % 12 == 1 || lsN % 12 == 5))
mbaPrimes[lsN] ^= true;
lsN -= lsX2;
if (lsN <= msLimit && lsN % 12 == 7)
mbaPrimes[lsN] ^= true;
if (lsX > lsY)
{
lsN -= lsY2 * 2;
if (lsN <= msLimit && lsN % 12 == 11)
mbaPrimes[lsN] ^= true;
}
}
}
}
for (int lsN = 5; lsN < lsSQRT; lsN += 2)
if (mbaPrimes[lsN])
{
var lsS = lsSquares[lsN];
for (int lsK = lsS; lsK <= msLimit; lsK += lsS)
mbaPrimes[lsK] = false;
}
}
}
}
And the CompartmentalisedParallel class:
using System;
using System.Threading.Tasks;
namespace PrimeGenerator
{
public static class CompartmentalisedParallel
{
#region Int
private static int[] CalculateCompartments(int startInclusive, int endExclusive, ref int threads)
{
if (threads == 0) threads = 1;
if (threads == -1) threads = Environment.ProcessorCount;
if (threads > endExclusive - startInclusive) threads = endExclusive - startInclusive;
int[] liThreadIndexes = new int[threads + 1];
liThreadIndexes[threads] = endExclusive - 1;
int liIndexesPerThread = (endExclusive - startInclusive) / threads;
for (int liCount = 0; liCount < threads; liCount++)
liThreadIndexes[liCount] = liCount * liIndexesPerThread;
return liThreadIndexes;
}
public static void For<TLocal>(
int startInclusive, int endExclusive,
ParallelOptions parallelOptions,
Func<int, int, TLocal> localInit,
Func<int, ParallelLoopState, TLocal, TLocal> body,
Action<TLocal, int, int> localFinally,
int threads)
{
int[] liThreadIndexes = CalculateCompartments(startInclusive, endExclusive, ref threads);
if (threads > 1)
Parallel.For(
0, threads, parallelOptions,
(liThread, lsState) =>
{
TLocal llLocal = localInit(liThreadIndexes[liThread], liThreadIndexes[liThread + 1]);
for (int liCounter = liThreadIndexes[liThread]; liCounter < liThreadIndexes[liThread + 1]; liCounter++)
body(liCounter, lsState, llLocal);
localFinally(llLocal, liThreadIndexes[liThread], liThreadIndexes[liThread + 1]);
}
);
else
{
TLocal llLocal = localInit(startInclusive, endExclusive);
for (int liCounter = startInclusive; liCounter < endExclusive; liCounter++)
body(liCounter, null, llLocal);
localFinally(llLocal, startInclusive, endExclusive);
}
}
public static void For(
int startInclusive, int endExclusive,
ParallelOptions parallelOptions,
Action<int, ParallelLoopState> body,
int threads)
{
int[] liThreadIndexes = CalculateCompartments(startInclusive, endExclusive, ref threads);
if (threads > 1)
Parallel.For(
0, threads, parallelOptions,
(liThread, lsState) =>
{
for (int liCounter = liThreadIndexes[liThread]; liCounter < liThreadIndexes[liThread + 1]; liCounter++)
body(liCounter, lsState);
}
);
else
for (int liCounter = startInclusive; liCounter < endExclusive; liCounter++)
body(liCounter, null);
}
public static void For(
int startInclusive, int endExclusive,
ParallelOptions parallelOptions,
Action<int> body,
int threads)
{
int[] liThreadIndexes = CalculateCompartments(startInclusive, endExclusive, ref threads);
if (threads > 1)
Parallel.For(
0, threads, parallelOptions,
(liThread) =>
{
for (int liCounter = liThreadIndexes[liThread]; liCounter < liThreadIndexes[liThread + 1]; liCounter++)
body(liCounter);
}
);
else
for (int liCounter = startInclusive; liCounter < endExclusive; liCounter++)
body(liCounter);
}
public static void For(
int startInclusive, int endExclusive,
Action<int, ParallelLoopState> body,
int threads)
{
For(startInclusive, endExclusive, new ParallelOptions(), body, threads);
}
public static void For(
int startInclusive, int endExclusive,
Action<int> body,
int threads)
{
For(startInclusive, endExclusive, new ParallelOptions(), body, threads);
}
public static void For<TLocal>(
int startInclusive, int endExclusive,
Func<int, int, TLocal> localInit,
Func<int, ParallelLoopState, TLocal, TLocal> body,
Action<TLocal, int, int> localFinally,
int threads)
{
For<TLocal>(startInclusive, endExclusive, new ParallelOptions(), localInit, body, localFinally, threads);
}
#endregion
#region Long
private static long[] CalculateCompartments(long startInclusive, long endExclusive, ref long threads)
{
if (threads == 0) threads = 1;
if (threads == -1) threads = Environment.ProcessorCount;
if (threads > endExclusive - startInclusive) threads = endExclusive - startInclusive;
long[] liThreadIndexes = new long[threads + 1];
liThreadIndexes[threads] = endExclusive - 1;
long liIndexesPerThread = (endExclusive - startInclusive) / threads;
for (long liCount = 0; liCount < threads; liCount++)
liThreadIndexes[liCount] = liCount * liIndexesPerThread;
return liThreadIndexes;
}
public static void For<TLocal>(
long startInclusive, long endExclusive,
ParallelOptions parallelOptions,
Func<long, long, TLocal> localInit,
Func<long, ParallelLoopState, TLocal, TLocal> body,
Action<TLocal, long, long> localFinally,
long threads)
{
long[] liThreadIndexes = CalculateCompartments(startInclusive, endExclusive, ref threads);
if (threads > 1)
Parallel.For(
0, threads, parallelOptions,
(liThread, lsState) =>
{
TLocal llLocal = localInit(liThreadIndexes[liThread], liThreadIndexes[liThread + 1]);
for (long liCounter = liThreadIndexes[liThread]; liCounter < liThreadIndexes[liThread + 1]; liCounter++)
body(liCounter, lsState, llLocal);
localFinally(llLocal, liThreadIndexes[liThread], liThreadIndexes[liThread + 1]);
}
);
else
{
TLocal llLocal = localInit(startInclusive, endExclusive);
for (long liCounter = startInclusive; liCounter < endExclusive; liCounter++)
body(liCounter, null, llLocal);
localFinally(llLocal, startInclusive, endExclusive);
}
}
public static void For(
long startInclusive, long endExclusive,
ParallelOptions parallelOptions,
Action<long, ParallelLoopState> body,
long threads)
{
long[] liThreadIndexes = CalculateCompartments(startInclusive, endExclusive, ref threads);
if (threads > 1)
Parallel.For(
0, threads, parallelOptions,
(liThread, lsState) =>
{
for (long liCounter = liThreadIndexes[liThread]; liCounter < liThreadIndexes[liThread + 1]; liCounter++)
body(liCounter, lsState);
}
);
else
for (long liCounter = startInclusive; liCounter < endExclusive; liCounter++)
body(liCounter, null);
}
public static void For(
long startInclusive, long endExclusive,
ParallelOptions parallelOptions,
Action<long> body,
long threads)
{
long[] liThreadIndexes = CalculateCompartments(startInclusive, endExclusive, ref threads);
if (threads > 1)
Parallel.For(
0, threads, parallelOptions,
(liThread) =>
{
for (long liCounter = liThreadIndexes[liThread]; liCounter < liThreadIndexes[liThread + 1]; liCounter++)
body(liCounter);
}
);
else
for (long liCounter = startInclusive; liCounter < endExclusive; liCounter++)
body(liCounter);
}
public static void For(
long startInclusive, long endExclusive,
Action<long, ParallelLoopState> body,
long threads)
{
For(startInclusive, endExclusive, new ParallelOptions(), body, threads);
}
public static void For(
long startInclusive, long endExclusive,
Action<long> body,
long threads)
{
For(startInclusive, endExclusive, new ParallelOptions(), body, threads);
}
public static void For<TLocal>(
long startInclusive, long endExclusive,
Func<long, long, TLocal> localInit,
Func<long, ParallelLoopState, TLocal, TLocal> body,
Action<TLocal, long, long> localFinally,
long threads)
{
For<TLocal>(startInclusive, endExclusive, new ParallelOptions(), localInit, body, localFinally, threads);
}
#endregion
}
}
Primes base class:
using System.Collections;
using System.Collections.Generic;
namespace PrimeGenerator
{
public abstract class Primes : IEnumerable<int>
{
protected readonly int msLimit;
public Primes(int limit)
{
msLimit = limit;
}
public int Limit
{
get
{
return msLimit;
}
}
public int Count
{
get
{
int liCount = 0;
foreach (int liPrime in this)
liCount++;
return liCount;
}
}
public abstract IEnumerator<int> GetEnumerator();
IEnumerator IEnumerable.GetEnumerator()
{
return GetEnumerator();
}
}
}
Use it by doing the following:
var lpPrimes = new Atkin(count, true);
Console.WriteLine(lpPrimes.Count);
Console.WriteLine(s.ElapsedMilliseconds);
However, i found the Eratosthenes to be quicker in all cases, even with a four core CPU running in multithreaded mode for the Atkin:
using System;
using System.Collections;
using System.Collections.Generic;
namespace PrimeGenerator
{
public class Eratosthenes : Primes
{
protected BitArray mbaOddEliminated;
public Eratosthenes(int limit)
: base(limit)
{
if (mbaOddEliminated == null) FindPrimes();
}
public override IEnumerator<int> GetEnumerator()
{
yield return 2;
for (int lsN = 3; lsN <= msLimit; lsN+=2)
if (!mbaOddEliminated[lsN>>1]) yield return lsN;
}
private void FindPrimes()
{
mbaOddEliminated = new BitArray((msLimit>>1) + 1);
int lsSQRT = (int)Math.Sqrt(msLimit);
for (int lsN = 3; lsN < lsSQRT + 1; lsN += 2)
if (!mbaOddEliminated[lsN>>1])
for (int lsM = lsN*lsN; lsM <= msLimit; lsM += lsN<<1)
mbaOddEliminated[lsM>>1] = true;
}
}
}
If you get the Atkin to run faster, please let me know!
回答6:
Heres an improvement of the Sieve of Eratosthenes using custom FixBitArrays and unsafe code for speed results, this is about 225% faster than my previous Eratosthenes algorithm, and the class is standalone (this is not multithreaded - Eratosthenes is not compatible with multi threading), On an AMD Phenom II X4 965 Processor I can calculate Primes to 1,000,000,000 limit in 9,261 ms:
using System;
using System.Collections;
using System.Collections.Generic;
namespace PrimeGenerator
{
// The block element type for the bit array,
// use any unsigned value. WARNING: UInt64 is
// slower even on x64 architectures.
using BitArrayType = System.UInt32;
// This should never be any bigger than 256 bits - leave as is.
using BitsPerBlockType = System.Byte;
// The prime data type, this can be any unsigned value, the limit
// of this type determines the limit of Prime value that can be
// found. WARNING: UInt64 is slower even on x64 architectures.
using PrimeType = System.UInt32;
/// <summary>
/// Calculates prime number using the Sieve of Eratosthenes method.
/// </summary>
/// <example>
/// <code>
/// var lpPrimes = new Eratosthenes(1e7);
/// foreach (UInt32 luiPrime in lpPrimes)
/// Console.WriteLine(luiPrime);
/// </example>
public class Eratosthenes : IEnumerable<PrimeType>
{
#region Constants
/// <summary>
/// Constant for number of bits per block, calculated based on size of BitArrayType.
/// </summary>
const BitsPerBlockType cbBitsPerBlock = sizeof(BitArrayType) * 8;
#endregion
#region Protected Locals
/// <summary>
/// The limit for the maximum prime value to find.
/// </summary>
protected readonly PrimeType mpLimit;
/// <summary>
/// The current bit array where a set bit means
/// the odd value at that location has been determined
/// to not be prime.
/// </summary>
protected BitArrayType[] mbaOddNotPrime;
#endregion
#region Initialisation
/// <summary>
/// Create Sieve of Eratosthenes generator.
/// </summary>
/// <param name="limit">The limit for the maximum prime value to find.</param>
public Eratosthenes(PrimeType limit)
{
// Check limit range
if (limit > PrimeType.MaxValue - (PrimeType)Math.Sqrt(PrimeType.MaxValue))
throw new ArgumentOutOfRangeException();
mpLimit = limit;
FindPrimes();
}
#endregion
#region Private Methods
/// <summary>
/// Finds the prime number within range.
/// </summary>
private unsafe void FindPrimes()
{
// Allocate bit array.
mbaOddNotPrime = new BitArrayType[(((mpLimit >> 1) + 1) / cbBitsPerBlock) + 1];
// Cache Sqrt of limit.
PrimeType lpSQRT = (PrimeType)Math.Sqrt(mpLimit);
// Fix the bit array for pointer access
fixed (BitArrayType* lpbOddNotPrime = &mbaOddNotPrime[0])
// Scan primes up to lpSQRT
for (PrimeType lpN = 3; lpN <= lpSQRT; lpN += 2)
// If the current bit value for index lpN is cleared (prime)
if (
(
lpbOddNotPrime[(lpN >> 1) / cbBitsPerBlock] &
((BitArrayType)1 << (BitsPerBlockType)((lpN >> 1) % cbBitsPerBlock))
) == 0
)
// Leave it cleared (prime) and mark all multiples of lpN*2 from lpN*lpN as not prime
for (PrimeType lpM = lpN * lpN; lpM <= mpLimit; lpM += lpN << 1)
// Set as not prime
lpbOddNotPrime[(lpM >> 1) / cbBitsPerBlock] |=
(BitArrayType)((BitArrayType)1 << (BitsPerBlockType)((lpM >> 1) % cbBitsPerBlock));
}
/// <summary>
/// Gets a bit value by index.
/// </summary>
/// <param name="bits">The blocks containing the bits.</param>
/// <param name="index">The index of the bit.</param>
/// <returns>True if bit is set, false if cleared.</returns>
private bool GetBitSafe(BitArrayType[] bits, PrimeType index)
{
return (bits[index / cbBitsPerBlock] & ((BitArrayType)1 << (BitsPerBlockType)(index % cbBitsPerBlock))) != 0;
}
#endregion
#region Public Properties
/// <summary>
/// Get the limit for the maximum prime value to find.
/// </summary>
public PrimeType Limit
{
get
{
return mpLimit;
}
}
/// <summary>
/// Returns the number of primes found in the range.
/// </summary>
public PrimeType Count
{
get
{
PrimeType lptCount = 0;
foreach (PrimeType liPrime in this)
lptCount++;
return lptCount;
}
}
/// <summary>
/// Determines if a value in range is prime or not.
/// </summary>
/// <param name="test">The value to test for primality.</param>
/// <returns>True if the value is prime, false otherwise.</returns>
public bool this[PrimeType test]
{
get
{
if (test > mpLimit) throw new ArgumentOutOfRangeException();
if (test <= 1) return false;
if (test == 2) return true;
if ((test & 1) == 0) return false;
return !GetBitSafe(mbaOddNotPrime, test >> 1);
}
}
#endregion
#region Public Methods
/// <summary>
/// Gets the enumerator for the primes.
/// </summary>
/// <returns>The enumerator of the primes.</returns>
public IEnumerator<PrimeType> GetEnumerator()
{
// Two always prime.
yield return 2;
// Start at first block, second MSB.
int liBlock = 0;
byte lbBit = 1;
BitArrayType lbaCurrent = mbaOddNotPrime[0] >> 1;
// For each value in range stepping in incrments of two for odd values.
for (PrimeType lpN = 3; lpN <= mpLimit; lpN += 2)
{
// If current bit not set then value is prime.
if ((lbaCurrent & 1) == 0)
yield return lpN;
// Move to NSB.
lbaCurrent >>= 1;
// Increment bit value.
lbBit++;
// If block is finished.
if (lbBit == cbBitsPerBlock)
{
// Move to first bit of next block.
lbBit = 0;
liBlock++;
lbaCurrent = mbaOddNotPrime[liBlock];
}
}
}
#endregion
#region IEnumerable<PrimeType> Implementation
/// <summary>
/// Gets the enumerator for the primes.
/// </summary>
/// <returns>The enumerator for the prime numbers.</returns>
IEnumerator IEnumerable.GetEnumerator()
{
return GetEnumerator();
}
#endregion
}
}
Primes found in 1,000,000,000: 50,847,534 in 9,261 ms
来源：https://stackoverflow.com/questions/1569127/c-implementation-of-the-sieve-of-atkin