I believe this improves sieve cache performance with the bit-vec crate, although I've some hiccup with cargo bench for testing this. This also fixes the confusing reference in #11

➜  vdf git:(master) cargo install
error: `/Users/user/r/vdf` is not a crate root; specify a crate to install from crates.io, or use --path or --git to specify an alternate source

Caused by:
  found a virtual manifest at `/Users/user/r/vdf/Cargo.toml` instead of a package manifest

May I ask why in https://github.com/poanetwork/vdf/blob/master/vdf/src/proof_pietrzak.rs#L45-L58

the iteration number has to be even and >=66? I couldn't find evidence for it in:

• https://eprint.iacr.org/2018/627.pdf
• https://eprint.iacr.org/2018/712.pdf

In https://github.com/poanetwork/vdf/blob/master/vdf/src/create_discriminant.rs#L60 you choose a prime of the form n + m x where m has many small prime factors https://github.com/poanetwork/vdf/blob/master/vdf/build.rs#L82

How does m having many prime factors improve uniformity for the prime? You site https://eprint.iacr.org/2011/401.pdf but I do not really know that literature so no explination jumped out at me.

I suppose the second hashing-to-a-prime function hash_prime in https://github.com/poanetwork/vdf/blob/master/vdf/src/proof_wesolowski.rs#L112 can use a simpler algorithm because it generates only 128 bit primes.

I just want to develop a wrapper for golang , so trying to run with "cargo test", and the first and second asserts all failed

extern crate vdf;

#[cfg(test)]
mod tests {
    #[test]
    fn it_works() {
        use vdf::{InvalidProof, PietrzakVDFParams, VDFParams, WesolowskiVDFParams, VDF};
        // The length of the prime numbers generated, in bits.
        const CORRECT_SOLUTION: &[u8] =
            b"\x00\x52\x71\xe8\xf9\xab\x2e\xb8\xa2\x90\x6e\x85\x1d\xfc\xb5\x54\x2e\x41\x73\xf0\x16\
         \xb8\x5e\x29\xd4\x81\xa1\x08\xdc\x82\xed\x3b\x3f\x97\x93\x7b\x7a\xa8\x24\x80\x11\x38\
         \xd1\x77\x1d\xea\x8d\xae\x2f\x63\x97\xe7\x6a\x80\x61\x3a\xfd\xa3\x0f\x2c\x30\xa3\x4b\
         \x04\x0b\xaa\xaf\xe7\x6d\x57\x07\xd6\x86\x89\x19\x3e\x5d\x21\x18\x33\xb3\x72\xa6\xa4\
         \x59\x1a\xbb\x88\xe2\xe7\xf2\xf5\xa5\xec\x81\x8b\x57\x07\xb8\x6b\x8b\x2c\x49\x5c\xa1\
         \x58\x1c\x17\x91\x68\x50\x9e\x35\x93\xf9\xa1\x68\x79\x62\x0a\x4d\xc4\xe9\x07\xdf\x45\
         \x2e\x8d\xd0\xff\xc4\xf1\x99\x82\x5f\x54\xec\x70\x47\x2c\xc0\x61\xf2\x2e\xb5\x4c\x48\
         \xd6\xaa\x5a\xf3\xea\x37\x5a\x39\x2a\xc7\x72\x94\xe2\xd9\x55\xdd\xe1\xd1\x02\xae\x2a\
         \xce\x49\x42\x93\x49\x2d\x31\xcf\xf2\x19\x44\xa8\xbc\xb4\x60\x89\x93\x06\x5c\x9a\x00\
         \x29\x2e\x8d\x3f\x46\x04\xe7\x46\x5b\x4e\xee\xfb\x49\x4f\x5b\xea\x10\x2d\xb3\x43\xbb\
         \x61\xc5\xa1\x5c\x7b\xdf\x28\x82\x06\x88\x5c\x13\x0f\xa1\xf2\xd8\x6b\xf5\xe4\x63\x4f\
         \xdc\x42\x16\xbc\x16\xef\x7d\xac\x97\x0b\x0e\xe4\x6d\x69\x41\x6f\x9a\x9a\xce\xe6\x51\
         \xd1\x58\xac\x64\x91\x5b";

        let num_bits: u16 = 2048;

        // An instance of the VDF.  Instances can be used arbitrarily many times.
        let pietrzak_vdf = PietrzakVDFParams(num_bits).new();

        // Solve for the correct answer.  This will take a minute or two.
        assert_eq!(
            &pietrzak_vdf.solve(b"\xaa", 10000).unwrap()[..],
            CORRECT_SOLUTION
        );

        // Verify the answer.  This should be far faster (less than a second).
        assert!(pietrzak_vdf
            .verify(b"\xaa", 10000, CORRECT_SOLUTION)
            .is_ok());
    }
}

the test mod pops up message as follows:

assert 1:

running 1 test
test tests::it_works ... FAILED

failures:

---- tests::it_works stdout ----
thread 'tests::it_works' panicked at 'assertion failed: `(left == right)`
  left: `[0, 24, 200, 140, 34, 152, 38, 114, 221, 25, 185, 125, 182, 169, 248, 182, 212, 14, 7, 2, 35, 97, 15, 19, 47, 152, 30, 30, 213, 129, 213, 94, 59, 193, 11, 249, 24, 2, 153, 3, 175, 64, 54, 155, 177, 191, 50, 81, 158, 1, 191, 219, 236, 104, 95, 110, 95, 114, 22, 212, 192, 208, 50, 25, 126, 12, 188, 176, 51, 76, 16, 242, 112, 168, 59, 76, 38, 68, 223, 65, 235, 58, 112, 212, 169, 224, 168, 205, 12, 173, 6, 235, 126, 140, 152, 95, 169, 147, 182, 128, 13, 243, 74, 254, 133, 137, 150, 188, 44, 230, 188, 216, 167, 39, 229, 131, 23, 133, 142, 11, 90, 215, 166, 20, 126, 232, 166, 67, 242, 0, 11, 4, 34, 31, 99, 140, 21, 175, 225, 167, 176, 93, 180, 173, 132, 12, 86, 188, 193, 66, 139, 64, 109, 86, 96, 104, 180, 127, 234, 112, 210, 131, 38, 200, 14, 86, 185, 200, 33, 219, 129, 101, 30, 169, 46, 8, 122, 41, 5, 55, 206, 152, 131, 148, 0, 62, 38, 211, 87, 222, 232, 155, 58, 193, 234, 5, 205, 160, 8, 236, 163, 59, 127, 144, 135, 88, 19, 215, 208, 22, 27, 186, 2, 69, 49, 63, 182, 55, 196, 68, 112, 244, 173, 136, 137, 98, 86, 252, 41, 189, 246, 151, 178, 246, 151, 112, 38, 93, 235, 21, 253, 175, 169, 7, 85, 246, 155, 7, 92, 193, 177, 108, 100, 46, 57, 149, 195, 133, 0, 71, 186, 196, 250, 85, 89, 156, 192, 170, 58, 152, 209, 198, 8, 141, 84, 26, 190, 200, 124, 218, 225, 39, 187, 147, 90, 123, 210, 242, 18, 5, 159, 34, 142, 87, 200, 153, 220, 149, 203, 232, 223, 172, 219, 22, 211, 232, 29, 143, 193, 142, 182, 79, 254, 205, 7, 83, 45, 127, 163, 229, 155, 125, 168, 134, 71, 71, 137, 248, 66, 243, 133, 26, 67, 84, 196, 35, 237, 3, 224, 4, 88, 236, 113, 120, 222, 56, 88, 167, 99, 108, 163, 47, 217, 19, 16, 197, 183, 119, 180, 115, 160, 218, 6, 126, 56, 135, 201, 153, 249, 8, 44, 55, 26, 174, 194, 153, 90, 138, 171, 10, 0, 28, 97, 147, 87, 238, 221, 255, 223, 9, 210, 221, 243, 171, 127, 47, 58, 158, 38, 38, 87, 182, 117, 80, 192, 13, 214, 42, 39, 71, 64, 126, 141, 149, 52, 118, 163, 7, 76, 210, 223, 175, 77, 131, 57, 84, 81, 64, 159, 255, 140, 34, 20, 18, 143, 203, 19, 31, 55, 154, 200, 51, 172, 182, 3, 202, 111, 66, 44, 240, 223, 70, 102, 213, 127, 127, 170, 164, 160, 92, 42, 164, 191, 221, 130, 3, 126, 184, 20, 117, 121, 85, 86, 91, 177, 146, 70, 199, 219, 111, 38, 205, 200, 181, 104, 158, 14, 84, 213, 24, 192, 17, 155, 21, 34, 240, 189, 153, 120, 130, 128, 192, 78, 27, 107, 34, 160, 65, 22, 58, 252, 103, 220, 178, 241, 9, 0, 49, 150, 95, 25, 244, 61, 35, 221, 154, 192, 187, 128, 209, 182, 235, 154, 86, 199, 127, 182, 77, 54, 101, 203, 182, 184, 62, 41, 157, 246, 197, 161, 229, 54, 162, 50, 223, 104, 37, 21, 229, 80, 49, 178, 222, 27, 66, 31, 78, 79, 166, 165, 161, 181, 84, 179, 217, 214, 80, 116, 57, 71, 242, 1, 32, 113, 187, 111, 66, 41, 1, 167, 48, 93, 55, 108, 129, 208, 81, 126, 38, 239, 174, 24, 85, 44, 81, 67, 178, 113, 110, 110, 206, 72, 200, 231, 32, 66, 142, 86, 201, 76, 211, 18, 177, 223, 11, 236, 6, 57, 188, 249, 23, 120, 164, 138, 146, 14, 172, 225, 124, 177, 190, 115, 157, 2, 180, 22, 0, 14, 226, 106, 252, 34, 93, 35, 242, 235, 233, 156, 34, 158, 111, 64, 100, 117, 60, 161, 87, 37, 125, 33, 194, 173, 226, 157, 128, 125, 19, 206, 112, 206, 20, 148, 6, 32, 40, 88, 85, 209, 4, 140, 225, 5, 32, 219, 101, 78, 124, 178, 212, 93, 12, 25, 62, 63, 41, 221, 165, 37, 244, 252, 249, 26, 118, 38, 152, 154, 52, 42, 248, 198, 115, 45, 65, 83, 130, 118, 180, 217, 227, 135, 36, 96, 112, 52, 83, 99, 164, 183, 180, 42, 137, 194, 218, 32, 49, 215, 141, 162, 187, 203, 91, 175, 10, 55, 251, 122, 5, 13, 45, 101, 254, 179, 199, 10, 115, 142, 183, 145, 107, 253, 248, 69, 45, 90, 5, 0, 52, 94, 181, 240, 239, 85, 41, 174, 33, 132, 139, 25, 167, 90, 48, 195, 250, 87, 180, 147, 205, 216, 96, 119, 234, 134, 127, 129, 210, 82, 21, 175, 159, 89, 92, 206, 16, 210, 195, 111, 178, 255, 84, 202, 208, 242, 249, 111, 71, 241, 174, 130, 116, 245, 114, 240, 215, 17, 190, 89, 0, 57, 67, 33, 205, 36, 130, 76, 63, 152, 172, 154, 2, 16, 128, 244, 185, 52, 159, 16, 7, 81, 115, 5, 138, 216, 242, 82, 145, 227, 46, 69, 176, 89, 56, 209, 175, 208, 20, 189, 16, 182, 118, 33, 229, 201, 73, 7, 177, 32, 1, 152, 243, 153, 225, 216, 146, 113, 198, 30, 229, 215, 219, 111, 9, 243, 151, 102, 0, 38, 75, 142, 56, 231, 43, 141, 80, 42, 11, 13, 223, 123, 115, 62, 42, 163, 212, 78, 37, 227, 154, 13, 112, 207, 225, 249, 211, 213, 29, 81, 230, 52, 152, 123, 139, 234, 45, 131, 255, 116, 23, 127, 168, 62, 95, 166, 95, 17, 88, 110, 86, 227, 248, 87, 73, 155, 92, 190, 129, 170, 34, 177, 55, 180, 192, 39, 165, 165, 71, 219, 111, 34, 228, 210, 235, 247, 84, 61, 106, 118, 146, 93, 65, 97, 85, 39, 160, 120, 79, 241, 143, 129, 206, 107, 4, 83, 123, 240, 29, 219, 170, 74, 107, 29, 0, 86, 139, 107, 218, 97, 241, 156, 161, 59, 105, 141, 106, 47, 165, 234, 156, 1, 236, 196, 147, 62, 231, 0, 82, 19, 166, 1, 109, 69, 107, 172, 246, 25, 146, 229, 221, 68, 248, 50, 188, 145, 130, 245, 189, 255, 225, 132, 7, 189, 84, 147, 214, 116, 154, 161, 221, 26, 96, 112, 172, 47, 233, 50, 17, 98, 211, 225, 183, 92, 119, 161, 137, 44, 88, 43, 213, 11, 61, 140, 85, 211, 50, 20, 141, 66, 203, 108, 11, 164, 5, 173, 84, 17, 167, 70, 67, 82, 246, 185, 97, 244, 25, 26, 203, 189, 198, 248, 249, 177, 221, 180, 116, 245, 193, 173, 227, 93, 113, 2, 195, 223, 154, 77, 199, 76, 238, 87, 121, 207, 97, 134, 33, 146, 231, 241, 37, 14, 165, 30, 57, 177, 189, 130, 193, 159, 160, 145, 180, 178, 0, 163, 255, 223, 27, 184, 65, 3, 73, 75, 2, 236, 182, 229, 89, 106, 230, 108, 7, 56, 14, 58, 55, 52, 42, 26, 140, 167, 126, 3, 133, 19, 218, 59, 55, 216, 149, 168, 165, 168, 133, 106, 13, 190, 210, 228, 92, 124, 71, 188, 33, 189, 115, 187, 53, 183, 179, 159, 205, 193, 101, 21, 212, 189, 249, 231, 56, 8, 171, 136, 25, 63, 156, 255, 0, 187, 230, 125, 92, 74, 55, 220, 234, 212, 190, 193, 83, 39, 34, 113, 54, 226, 121, 210, 40, 201, 215, 250, 176, 227, 76, 67, 132, 148, 9, 106, 138, 4, 133, 221, 88, 110, 211, 243, 53, 192, 62, 220, 217, 59, 95, 54, 150, 55, 99, 248, 245, 182, 185, 25, 233, 0, 0, 235, 230, 79, 16, 1, 9, 223, 200, 58, 132, 248, 67, 29, 137, 25, 133, 164, 5, 81, 76, 95, 100, 87, 57, 40, 42, 252, 92, 249, 100, 200, 151, 128, 51, 58, 112, 117, 145, 141, 237, 79, 233, 255, 16, 183, 249, 151, 191, 77, 105, 215, 40, 147, 184, 250, 86, 210, 9, 169, 117, 49, 107, 210, 242, 24, 245, 35, 64, 245, 198, 7, 144, 199, 87, 124, 245, 198, 191, 198, 169, 101, 173, 237, 141, 219, 72, 40, 112, 119, 232, 251, 127, 92, 18, 89, 96, 147, 99, 223, 248, 13, 97, 171, 197, 132, 179, 218, 66, 96, 247, 232, 149, 154, 182, 181, 238, 121, 86, 236, 211, 80, 51, 42, 176, 50, 252, 199, 0, 0, 138, 153, 192, 52, 210, 223, 194, 137, 115, 236, 168, 40, 30, 205, 71, 10, 53, 97, 127, 59, 142, 250, 211, 111, 43, 237, 54, 110, 63, 150, 107, 214, 120, 96, 253, 23, 20, 124, 249, 101, 240, 250, 141, 85, 213, 171, 255, 174, 145, 61, 9, 235, 221, 184, 4, 57, 31, 242, 59, 35, 251, 74, 253, 251, 63, 85, 188, 145, 239, 157, 200, 93, 179, 202, 201, 208, 211, 188, 63, 83, 109, 92, 29, 42, 6, 133, 67, 123, 106, 108, 136, 30, 197, 205, 201, 175, 152, 181, 8, 26, 182, 52, 167, 59, 65, 154, 105, 39, 175, 191, 114, 34, 60, 36, 95, 135, 253, 80, 22, 73, 171, 184, 216, 240, 36, 23, 105, 0, 19, 8, 67, 207, 18, 3, 138, 144, 68, 171, 239, 236, 212, 227, 188, 199, 50, 9, 145, 251, 146, 203, 111, 29, 220, 126, 48, 172, 206, 198, 227, 76, 179, 54, 92, 48, 136, 162, 142, 76, 158, 73, 140, 80, 92, 163, 196, 75, 158, 156, 227, 58, 31, 187, 248, 217, 77, 74, 50, 101, 137, 91, 123, 223, 81, 189, 45, 17, 240, 216, 182, 195, 108, 69, 128, 58, 33, 217, 24, 201, 121, 139, 141, 128, 144, 99, 236, 66, 210, 27, 138, 123, 75, 10, 240, 31, 8, 69, 248, 222, 40, 13, 223, 109, 129, 38, 145, 189, 216, 118, 111, 223, 117, 136, 172, 49, 136, 94, 192, 224, 125, 220, 14, 51, 217, 75, 25, 60, 0, 17, 90, 136, 133, 198, 10, 32, 180, 200, 129, 149, 213, 126, 158, 71, 156, 234, 154, 217, 114, 2, 214, 231, 46, 200, 42, 52, 213, 48, 141, 56, 194, 117, 96, 147, 174, 232, 255, 124, 60, 30, 46, 197, 103, 48, 19, 227, 234, 166, 0, 138, 63, 204, 97, 238, 238, 79, 178, 234, 215, 67, 62, 125, 29, 73, 242, 85, 14, 3, 134, 22, 218, 138, 184, 248, 201, 155, 33, 86, 90, 208, 24, 202, 156, 210, 67, 251, 8, 106, 14, 57, 126, 205, 27, 42, 209, 74, 72, 212, 175, 199, 124, 5, 92, 93, 98, 76, 236, 46, 191, 147, 28, 209, 201, 24, 20, 3, 200, 65, 103, 138, 73, 61, 212, 32, 145, 148, 67, 0, 49, 80, 94, 59, 86, 203, 219, 145, 84, 64, 111, 253, 149, 234, 34, 187, 24, 222, 78, 176, 52, 35, 253, 179, 110, 236, 189, 189, 164, 112, 57, 205, 216, 172, 30, 166, 55, 251, 128, 81, 192, 180, 49, 40, 174, 116, 171, 18, 48, 113, 187, 59, 15, 174, 202, 119, 23, 89, 192, 225, 115, 37, 8, 207, 38, 124, 113, 100, 102, 222, 233, 247, 53, 122, 233, 128, 136, 40, 67, 26, 93, 226, 165, 58, 11, 71, 1, 48, 27, 152, 206, 54, 245, 50, 203, 79, 234, 249, 35, 192, 62, 79, 51, 31, 218, 241, 48, 68, 192, 130, 245, 9, 69, 128, 150, 191, 71, 34, 153, 92, 181, 82, 127, 72, 170, 183, 35, 183, 255, 233, 14, 52, 229, 62, 47, 105, 173, 206, 205, 151, 31, 55, 77, 252, 205, 2, 82, 128, 203, 118, 48, 193, 213, 133, 155, 123, 108, 181, 19, 138, 176, 139, 139, 165, 62, 138, 212, 198, 149, 103, 13, 115, 70, 183, 220, 44, 90, 91, 173, 65, 22, 202, 190, 12, 193, 27, 0, 151, 249, 170, 3, 23, 191, 98, 144, 184, 179, 241, 154, 186, 5, 194, 121, 189, 195, 20, 225, 41, 63, 190, 189, 3, 3, 236, 179, 5, 223, 243, 217, 58, 254, 175, 253, 113, 179, 122, 95, 99, 73, 3, 148, 48, 15, 112, 38, 141, 59, 164, 156, 163, 176, 150, 37, 92, 235, 109, 25, 72, 188, 115, 227, 133, 85, 76, 243, 13, 103]`,
 right: `[0, 82, 113, 232, 249, 171, 46, 184, 162, 144, 110, 133, 29, 252, 181, 84, 46, 65, 115, 240, 22, 184, 94, 41, 212, 129, 161, 8, 220, 130, 237, 59, 63, 151, 147, 123, 122, 168, 36, 128, 17, 56, 209, 119, 29, 234, 141, 174, 47, 99, 151, 231, 106, 128, 97, 58, 253, 163, 15, 44, 48, 163, 75, 4, 11, 170, 175, 231, 109, 87, 7, 214, 134, 137, 25, 62, 93, 33, 24, 51, 179, 114, 166, 164, 89, 26, 187, 136, 226, 231, 242, 245, 165, 236, 129, 139, 87, 7, 184, 107, 139, 44, 73, 92, 161, 88, 28, 23, 145, 104, 80, 158, 53, 147, 249, 161, 104, 121, 98, 10, 77, 196, 233, 7, 223, 69, 46, 141, 208, 255, 196, 241, 153, 130, 95, 84, 236, 112, 71, 44, 192, 97, 242, 46, 181, 76, 72, 214, 170, 90, 243, 234, 55, 90, 57, 42, 199, 114, 148, 226, 217, 85, 221, 225, 209, 2, 174, 42, 206, 73, 66, 147, 73, 45, 49, 207, 242, 25, 68, 168, 188, 180, 96, 137, 147, 6, 92, 154, 0, 41, 46, 141, 63, 70, 4, 231, 70, 91, 78, 238, 251, 73, 79, 91, 234, 16, 45, 179, 67, 187, 97, 197, 161, 92, 123, 223, 40, 130, 6, 136, 92, 19, 15, 161, 242, 216, 107, 245, 228, 99, 79, 220, 66, 22, 188, 22, 239, 125, 172, 151, 11, 14, 228, 109, 105, 65, 111, 154, 154, 206, 230, 81, 209, 88, 172, 100, 145, 91]`', src/lib.rs:30:9
note: run with `RUST_BACKTRACE=1` environment variable to display a backtrace


failures:
    tests::it_works

test result: FAILED. 0 passed; 1 failed; 0 ignored; 0 measured; 0 filtered out; finished in 2.10s

assert 2:

thread 'tests::it_works' panicked at 'assertion failed: pietrzak_vdf.verify(b\"\\xaa\", 10000, CORRECT_SOLUTION).is_ok()', src/lib.rs:36:9

https://github.com/poanetwork/vdf/blob/c740ef3b9a4b4663b672ada93bb1c9ba0c80a965/vdf/src/proof_wesolowski.rs#L69-L89

I search for "approximat" in https://eprint.iacr.org/2018/623.pdf and it leads me to section 3.1 and section 4.3. However, none of them seems implying the logic in the above codes.

Why calculate l & k this way? Which part of the paper should I refer to?

Both Pietrzak and Wesolowski functions are about 10-20x times slower on AMD CPUs:

Intel(R) Xeon(R) Platinum 8175M CPU @ 2.50GHz:

time vdf-cli -t pietrzak aa 100 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                                                                                                    
Proof is valid                                                                                                                       
                                                                                                                                     
real    0m0.944s
user    0m0.944s
sys     0m0.000s

AMD Ryzen 7 2700X Eight-Core Processor:

time vdf-cli -t pietrzak aa 100 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                                                                                                    
Proof is valid

real	0m12,991s
user	0m12,988s
sys	0m0,000s

cpuinfo:

processor	: 0
vendor_id	: AuthenticAMD
cpu family	: 23
model		: 8
model name	: AMD Ryzen 7 2700X Eight-Core Processor
stepping	: 2
microcode	: 0x800820b
cpu MHz		: 1822.593
cache size	: 512 KB
physical id	: 0
siblings	: 16
core id		: 0
cpu cores	: 8
apicid		: 0
initial apicid	: 0
fpu		: yes
fpu_exception	: yes
cpuid level	: 13
wp		: yes
flags		: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid aperfmperf pni pclmulqdq monitor ssse3 fma cx16 sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb hw_pstate sme ssbd sev ibpb vmmcall fsgsbase bmi1 avx2 smep bmi2 rdseed adx smap clflushopt sha_ni xsaveopt xsavec xgetbv1 xsaves clzero irperf xsaveerptr arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold avic v_vmsave_vmload vgif overflow_recov succor smca
bugs		: sysret_ss_attrs null_seg spectre_v1 spectre_v2 spec_store_bypass
bogomips	: 7385.43
TLB size	: 2560 4K pages
clflush size	: 64
cache_alignment	: 64
address sizes	: 43 bits physical, 48 bits virtual
power management: ts ttp tm hwpstate cpb eff_freq_ro [13] [14]

There are issues caused by dynamic linking if we try to build the crate to wasm32, see #16 for details. GMP can supports a musl target. We should support it too and allow static linking. That should hopefully resolve the issues with wasm32 linking.

Hi, I'm trying to compile VDF library to WebAssembly so that it can be used in Browser and Node.js enviroments for Subspace project. I'm having a lot of difficulties with this endeavor (some of the major pain points being glibc and gmp libraries), but hoping to get it working eventually.

Would you be interested in having WebAssembly support in this repo, helping in any way or any other thoughts on the topic? I'd prefer to upstream all the work in this direction so that it can be kept up to date with any changes happening to source code.

I'd suggest using either shake128 or blake2x for the two places where you sample considerable data in create_discriminant.rs and proof_wesolowski.rs. It's only a negligible impact on performance, but it just looks ugly to roll you own stream cipher with sha2.

We could easily use sha2 for hashing and chacha20 for output, but this requires using another crate and algorithm. Shake128 is a keccak based hash function together with an extensible output function (XOF). Blake2x is a chacha based hash with an XOF. So either gives everything requires with only one dependency.

I selected shake128 over blake2x based on prevalence and the promise that keccak implemented easily in hardware, which matters if this ever gets made into an ASIC. As an aside, shake128/shake256 are always preferred over SHA3 because NIST senselessly conflated security level with output bits in the SHA3 competition.

In this PR, I've only switched the usage in proof_wesolowski.rs so far because altering create_discriminant.rs would change the test vectors. If you've nothing in production, then we should change create_discriminant.rs too, and maybe remove test vectors until things stabilize. If anyone has this in production, then we should create a feature or something because even this PR breaks the non-existent test vectors for the VDF itself.