/** * zfec -- fast forward error correction library with Python interface */ #include "fec.h" #include #include #include #include /* * Primitive polynomials - see Lin & Costello, Appendix A, * and Lee & Messerschmitt, p. 453. */ static const char*const Pp="101110001"; /* * To speed up computations, we have tables for logarithm, exponent and * inverse of a number. We use a table for multiplication as well (it takes * 64K, no big deal even on a PDA, especially because it can be * pre-initialized an put into a ROM!), otherwhise we use a table of * logarithms. In any case the macro gf_mul(x,y) takes care of * multiplications. */ static gf gf_exp[510]; /* index->poly form conversion table */ static int gf_log[256]; /* Poly->index form conversion table */ static gf inverse[256]; /* inverse of field elem. */ /* inv[\alpha**i]=\alpha**(GF_SIZE-i-1) */ /* * modnn(x) computes x % GF_SIZE, where GF_SIZE is 2**GF_BITS - 1, * without a slow divide. */ static gf modnn(int x) { while (x >= 255) { x -= 255; x = (x >> 8) + (x & 255); } return x; } #define SWAP(a,b,t) {t tmp; tmp=a; a=b; b=tmp;} /* * gf_mul(x,y) multiplies two numbers. It is much faster to use a * multiplication table. * * USE_GF_MULC, GF_MULC0(c) and GF_ADDMULC(x) can be used when multiplying * many numbers by the same constant. In this case the first call sets the * constant, and others perform the multiplications. A value related to the * multiplication is held in a local variable declared with USE_GF_MULC . See * usage in _addmul1(). */ static gf gf_mul_table[256][256]; #define gf_mul(x,y) gf_mul_table[x][y] #define USE_GF_MULC register gf * __gf_mulc_ #define GF_MULC0(c) __gf_mulc_ = gf_mul_table[c] #define GF_ADDMULC(dst, x) dst ^= __gf_mulc_[x] /* * Generate GF(2**m) from the irreducible polynomial p(X) in p[0]..p[m] * Lookup tables: * index->polynomial form gf_exp[] contains j= \alpha^i; * polynomial form -> index form gf_log[ j = \alpha^i ] = i * \alpha=x is the primitive element of GF(2^m) * * For efficiency, gf_exp[] has size 2*GF_SIZE, so that a simple * multiplication of two numbers can be resolved without calling modnn */ static void _init_mul_table(void) { int i, j; for (i = 0; i < 256; i++) for (j = 0; j < 256; j++) gf_mul_table[i][j] = gf_exp[modnn (gf_log[i] + gf_log[j])]; for (j = 0; j < 256; j++) gf_mul_table[0][j] = gf_mul_table[j][0] = 0; } #define NEW_GF_MATRIX(rows, cols) \ (gf*)malloc(rows * cols) /* * initialize the data structures used for computations in GF. */ static void generate_gf (void) { int i; gf mask; mask = 1; /* x ** 0 = 1 */ gf_exp[8] = 0; /* will be updated at the end of the 1st loop */ /* * first, generate the (polynomial representation of) powers of \alpha, * which are stored in gf_exp[i] = \alpha ** i . * At the same time build gf_log[gf_exp[i]] = i . * The first 8 powers are simply bits shifted to the left. */ for (i = 0; i < 8; i++, mask <<= 1) { gf_exp[i] = mask; gf_log[gf_exp[i]] = i; /* * If Pp[i] == 1 then \alpha ** i occurs in poly-repr * gf_exp[8] = \alpha ** 8 */ if (Pp[i] == '1') gf_exp[8] ^= mask; } /* * now gf_exp[8] = \alpha ** 8 is complete, so can also * compute its inverse. */ gf_log[gf_exp[8]] = 8; /* * Poly-repr of \alpha ** (i+1) is given by poly-repr of * \alpha ** i shifted left one-bit and accounting for any * \alpha ** 8 term that may occur when poly-repr of * \alpha ** i is shifted. */ mask = 1 << 7; for (i = 9; i < 255; i++) { if (gf_exp[i - 1] >= mask) gf_exp[i] = gf_exp[8] ^ ((gf_exp[i - 1] ^ mask) << 1); else gf_exp[i] = gf_exp[i - 1] << 1; gf_log[gf_exp[i]] = i; } /* * log(0) is not defined, so use a special value */ gf_log[0] = 255; /* set the extended gf_exp values for fast multiply */ for (i = 0; i < 255; i++) gf_exp[i + 255] = gf_exp[i]; /* * again special cases. 0 has no inverse. This used to * be initialized to 255, but it should make no difference * since noone is supposed to read from here. */ inverse[0] = 0; inverse[1] = 1; for (i = 2; i <= 255; i++) inverse[i] = gf_exp[255 - gf_log[i]]; } /* * Various linear algebra operations that i use often. */ /* * addmul() computes dst[] = dst[] + c * src[] * This is used often, so better optimize it! Currently the loop is * unrolled 16 times, a good value for 486 and pentium-class machines. * The case c=0 is also optimized, whereas c=1 is not. These * calls are unfrequent in my typical apps so I did not bother. */ #define addmul(dst, src, c, sz) \ if (c != 0) _addmul1(dst, src, c, sz) #define UNROLL 16 /* 1, 4, 8, 16 */ static void _addmul1(register gf*restrict dst, const register gf*restrict src, gf c, size_t sz) { USE_GF_MULC; const gf* lim = &dst[sz - UNROLL + 1]; GF_MULC0 (c); #if (UNROLL > 1) /* unrolling by 8/16 is quite effective on the pentium */ for (; dst < lim; dst += UNROLL, src += UNROLL) { GF_ADDMULC (dst[0], src[0]); GF_ADDMULC (dst[1], src[1]); GF_ADDMULC (dst[2], src[2]); GF_ADDMULC (dst[3], src[3]); #if (UNROLL > 4) GF_ADDMULC (dst[4], src[4]); GF_ADDMULC (dst[5], src[5]); GF_ADDMULC (dst[6], src[6]); GF_ADDMULC (dst[7], src[7]); #endif #if (UNROLL > 8) GF_ADDMULC (dst[8], src[8]); GF_ADDMULC (dst[9], src[9]); GF_ADDMULC (dst[10], src[10]); GF_ADDMULC (dst[11], src[11]); GF_ADDMULC (dst[12], src[12]); GF_ADDMULC (dst[13], src[13]); GF_ADDMULC (dst[14], src[14]); GF_ADDMULC (dst[15], src[15]); #endif } #endif lim += UNROLL - 1; for (; dst < lim; dst++, src++) /* final components */ GF_ADDMULC (*dst, *src); } /* * computes C = AB where A is n*k, B is k*m, C is n*m */ static void _matmul(gf * a, gf * b, gf * c, unsigned n, unsigned k, unsigned m) { unsigned row, col, i; for (row = 0; row < n; row++) { for (col = 0; col < m; col++) { gf *pa = &a[row * k]; gf *pb = &b[col]; gf acc = 0; for (i = 0; i < k; i++, pa++, pb += m) acc ^= gf_mul (*pa, *pb); c[row * m + col] = acc; } } } /* * _invert_mat() takes a matrix and produces its inverse * k is the size of the matrix. * (Gauss-Jordan, adapted from Numerical Recipes in C) * Return non-zero if singular. */ static void _invert_mat(gf* src, unsigned k) { gf c, *p; unsigned irow = 0; unsigned icol = 0; unsigned row, col, i, ix; unsigned* indxc = (unsigned*) malloc (k * sizeof(unsigned)); unsigned* indxr = (unsigned*) malloc (k * sizeof(unsigned)); unsigned* ipiv = (unsigned*) malloc (k * sizeof(unsigned)); gf *id_row = NEW_GF_MATRIX (1, k); memset (id_row, '\0', k * sizeof (gf)); /* * ipiv marks elements already used as pivots. */ for (i = 0; i < k; i++) ipiv[i] = 0; for (col = 0; col < k; col++) { gf *pivot_row; /* * Zeroing column 'col', look for a non-zero element. * First try on the diagonal, if it fails, look elsewhere. */ if (ipiv[col] != 1 && src[col * k + col] != 0) { irow = col; icol = col; goto found_piv; } for (row = 0; row < k; row++) { if (ipiv[row] != 1) { for (ix = 0; ix < k; ix++) { if (ipiv[ix] == 0) { if (src[row * k + ix] != 0) { irow = row; icol = ix; goto found_piv; } } else assert (ipiv[ix] <= 1); } } } found_piv: ++(ipiv[icol]); /* * swap rows irow and icol, so afterwards the diagonal * element will be correct. Rarely done, not worth * optimizing. */ if (irow != icol) for (ix = 0; ix < k; ix++) SWAP (src[irow * k + ix], src[icol * k + ix], gf); indxr[col] = irow; indxc[col] = icol; pivot_row = &src[icol * k]; c = pivot_row[icol]; assert (c != 0); if (c != 1) { /* otherwhise this is a NOP */ /* * this is done often , but optimizing is not so * fruitful, at least in the obvious ways (unrolling) */ c = inverse[c]; pivot_row[icol] = 1; for (ix = 0; ix < k; ix++) pivot_row[ix] = gf_mul (c, pivot_row[ix]); } /* * from all rows, remove multiples of the selected row * to zero the relevant entry (in fact, the entry is not zero * because we know it must be zero). * (Here, if we know that the pivot_row is the identity, * we can optimize the addmul). */ id_row[icol] = 1; if (memcmp (pivot_row, id_row, k * sizeof (gf)) != 0) { for (p = src, ix = 0; ix < k; ix++, p += k) { if (ix != icol) { c = p[icol]; p[icol] = 0; addmul (p, pivot_row, c, k); } } } id_row[icol] = 0; } /* done all columns */ for (col = k; col > 0; col--) if (indxr[col-1] != indxc[col-1]) for (row = 0; row < k; row++) SWAP (src[row * k + indxr[col-1]], src[row * k + indxc[col-1]], gf); } /* * fast code for inverting a vandermonde matrix. * * NOTE: It assumes that the matrix is not singular and _IS_ a vandermonde * matrix. Only uses the second column of the matrix, containing the p_i's. * * Algorithm borrowed from "Numerical recipes in C" -- sec.2.8, but largely * revised for my purposes. * p = coefficients of the matrix (p_i) * q = values of the polynomial (known) */ void _invert_vdm (gf* src, unsigned k) { unsigned i, j, row, col; gf *b, *c, *p; gf t, xx; if (k == 1) /* degenerate case, matrix must be p^0 = 1 */ return; /* * c holds the coefficient of P(x) = Prod (x - p_i), i=0..k-1 * b holds the coefficient for the matrix inversion */ c = NEW_GF_MATRIX (1, k); b = NEW_GF_MATRIX (1, k); p = NEW_GF_MATRIX (1, k); for (j = 1, i = 0; i < k; i++, j += k) { c[i] = 0; p[i] = src[j]; /* p[i] */ } /* * construct coeffs. recursively. We know c[k] = 1 (implicit) * and start P_0 = x - p_0, then at each stage multiply by * x - p_i generating P_i = x P_{i-1} - p_i P_{i-1} * After k steps we are done. */ c[k - 1] = p[0]; /* really -p(0), but x = -x in GF(2^m) */ for (i = 1; i < k; i++) { gf p_i = p[i]; /* see above comment */ for (j = k - 1 - (i - 1); j < k - 1; j++) c[j] ^= gf_mul (p_i, c[j + 1]); c[k - 1] ^= p_i; } for (row = 0; row < k; row++) { /* * synthetic division etc. */ xx = p[row]; t = 1; b[k - 1] = 1; /* this is in fact c[k] */ for (i = k - 1; i > 0; i--) { b[i-1] = c[i] ^ gf_mul (xx, b[i]); t = gf_mul (xx, t) ^ b[i-1]; } for (col = 0; col < k; col++) src[col * k + row] = gf_mul (inverse[t], b[col]); } free (c); free (b); free (p); return; } static int fec_initialized = 0; static void init_fec (void) { generate_gf(); _init_mul_table(); fec_initialized = 1; } /* * This section contains the proper FEC encoding/decoding routines. * The encoding matrix is computed starting with a Vandermonde matrix, * and then transforming it into a systematic matrix. */ #define FEC_MAGIC 0xFECC0DEC void fec_free (fec_t *p) { assert (p != NULL && p->magic == (((FEC_MAGIC ^ p->k) ^ p->n) ^ (unsigned long) (p->enc_matrix))); free (p->enc_matrix); free (p); } fec_t * fec_new(unsigned k, unsigned n) { unsigned row, col; gf *p, *tmp_m; fec_t *retval; if (fec_initialized == 0) init_fec (); retval = (fec_t *) malloc (sizeof (fec_t)); retval->k = k; retval->n = n; retval->enc_matrix = NEW_GF_MATRIX (n, k); retval->magic = ((FEC_MAGIC ^ k) ^ n) ^ (unsigned long) (retval->enc_matrix); tmp_m = NEW_GF_MATRIX (n, k); /* * fill the matrix with powers of field elements, starting from 0. * The first row is special, cannot be computed with exp. table. */ tmp_m[0] = 1; for (col = 1; col < k; col++) tmp_m[col] = 0; for (p = tmp_m + k, row = 0; row < n - 1; row++, p += k) for (col = 0; col < k; col++) p[col] = gf_exp[modnn (row * col)]; /* * quick code to build systematic matrix: invert the top * k*k vandermonde matrix, multiply right the bottom n-k rows * by the inverse, and construct the identity matrix at the top. */ _invert_vdm (tmp_m, k); /* much faster than _invert_mat */ _matmul(tmp_m + k * k, tmp_m, retval->enc_matrix + k * k, n - k, k, k); /* * the upper matrix is I so do not bother with a slow multiply */ memset (retval->enc_matrix, '\0', k * k * sizeof (gf)); for (p = retval->enc_matrix, col = 0; col < k; col++, p += k + 1) *p = 1; free (tmp_m); return retval; } /* To make sure that we stay within cache in the inner loops of fec_encode() and fec_decode(). */ #define STRIDE 8192 void fec_encode(const fec_t* code, const gf*restrict const*restrict const src, gf*restrict const*restrict const fecs, const unsigned*restrict const block_nums, size_t num_block_nums, size_t sz) { unsigned char i, j; size_t k; unsigned fecnum; const gf* p; for (k = 0; k < sz; k += STRIDE) { size_t stride = ((sz-k) < STRIDE)?(sz-k):STRIDE; for (i=0; i= code->k); memset(fecs[i]+k, 0, stride); p = &(code->enc_matrix[fecnum * code->k]); for (j = 0; j < code->k; j++) addmul(fecs[i]+k, src[j]+k, p[j], stride); } } } /** * Build decode matrix into some memory space. * * @param matrix a space allocated for a k by k matrix */ void build_decode_matrix_into_space(const fec_t*restrict const code, const unsigned*const restrict index, const unsigned k, gf*restrict const matrix) { unsigned char i; gf* p; for (i=0, p=matrix; i < k; i++, p += k) { if (index[i] < k) { memset(p, 0, k); p[i] = 1; } else { memcpy(p, &(code->enc_matrix[index[i] * code->k]), k); } } _invert_mat (matrix, k); } void fec_decode(const fec_t* code, const gf*restrict const*restrict const inpkts, gf*restrict const*restrict const outpkts, const unsigned*restrict const index, size_t sz) { gf* m_dec = (gf*)alloca(code->k * code->k); unsigned char outix=0; unsigned char row=0; unsigned char col=0; build_decode_matrix_into_space(code, index, code->k, m_dec); for (row=0; rowk; row++) { assert ((index[row] >= code->k) || (index[row] == row)); /* If the block whose number is i is present, then it is required to be in the i'th element. */ if (index[row] >= code->k) { memset(outpkts[outix], 0, sz); for (col=0; col < code->k; col++) addmul(outpkts[outix], inpkts[col], m_dec[row * code->k + col], sz); outix++; } } } /** * zfec -- fast forward error correction library with Python interface * * Copyright (C) 2007 Allmydata, Inc. * Author: Zooko Wilcox-O'Hearn * * This file is part of zfec. * * See README.txt for licensing information. */ /* * This work is derived from the "fec" software by Luigi Rizzo, et al., the * copyright notice and licence terms of which are included below for reference. * fec.c -- forward error correction based on Vandermonde matrices 980624 (C) * 1997-98 Luigi Rizzo (luigi@iet.unipi.it) * * Portions derived from code by Phil Karn (karn@ka9q.ampr.org), * Robert Morelos-Zaragoza (robert@spectra.eng.hawaii.edu) and Hari * Thirumoorthy (harit@spectra.eng.hawaii.edu), Aug 1995 * * Modifications by Dan Rubenstein (see Modifications.txt for * their description. * Modifications (C) 1998 Dan Rubenstein (drubenst@cs.umass.edu) * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions * are met: * * 1. Redistributions of source code must retain the above copyright * notice, this list of conditions and the following disclaimer. * 2. Redistributions in binary form must reproduce the above * copyright notice, this list of conditions and the following * disclaimer in the documentation and/or other materials * provided with the distribution. * * THIS SOFTWARE IS PROVIDED BY THE AUTHORS ``AS IS'' AND * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, * THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A * PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE AUTHORS * BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, * OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, * PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, * OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY * THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR * TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT * OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY * OF SUCH DAMAGE. */