ae82e96f8c
done by Bill Paul) and various other BSD programs. Obtained from:FSF
185 lines
7.9 KiB
Plaintext
185 lines
7.9 KiB
Plaintext
THINGS TO WORK ON
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Note that many of these things mentioned here are already fixed in GMP 2.0.
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* Improve speed for non-gcc compilers by defining umul_ppmm, udiv_qrnnd,
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etc, to call __umul_ppmm, __udiv_qrnnd. A typical definition for
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umul_ppmm would be
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#define umul_ppmm(ph,pl,m0,m1) \
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{unsigned long __ph; (pl) = __umul_ppmm (&__ph, (m0), (m1)); (ph) = __ph;}
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In order to maintain just one version of longlong.h (gmp and gcc), this
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has to be done outside of longlong.h.
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* Change mpn-routines to not deal with normalisation?
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mpn_add: Unchanged.
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mpn_sub: Remove normalization loop. Does it assume normalised input?
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mpn_mul: Make it return most sign limb, to simplify normalisation.
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Karatsubas algorith will be greatly simplified if mpn_add and
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mpn_sub doesn't normalise their results.
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mpn_div: Still requires strict normalisation.
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Beware of problems with mpn_cmp (and similar), a larger size does not
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ensure that an operand is larger, since it may be "less normalised".
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Normalization has to be moved into mpz-functions.
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Bennet Yee at CMU proposes:
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* mpz_{put,get}_raw for memory oriented I/O like other *_raw functions.
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* A function mpfatal that is called for exceptions. The user may override
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the default definition.
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* mout should group in 10-digit groups.
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* ASCII dependence?
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* Error reporting from I/O functions (linkoping)?
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* Make all computation mpz_* functions return a signed int indicating if
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the result was zero, positive, or negative?
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* Implement mpz_cmpabs, mpz_xor, mpz_to_double, mpz_to_si, mpz_lcm,
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mpz_dpb, mpz_ldb, various bit string operations like mpz_cntbits. Also
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mpz_@_si for most @??
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Brian Beuning proposes:
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1. An array of small primes
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3. A function to factor an MINT
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4. A routine to look for "small" divisors of an MINT
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5. A 'multiply mod n' routine based on Montgomery's algorithm.
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Doug Lea proposes:
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1. A way to find out if an integer fits into a signed int, and if so, a
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way to convert it out.
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2. Similarly for double precision float conversion.
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3. A function to convert the ratio of two integers to a double. This
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can be useful for mixed mode operations with integers, rationals, and
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doubles.
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5. Bit-setting, clearing, and testing operations, as in
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mpz_setbit(MP_INT* dest, MP_INT* src, unsigned long bit_number),
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and used, for example in
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mpz_setbit(x, x, 123)
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to directly set the 123rd bit of x.
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If these are supported, you don't first have to set up
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an otherwise unnecessary mpz holding a shifted value, then
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do an "or" operation.
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Elliptic curve method descrition in the Chapter `Algorithms in Number
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Theory' in the Handbook of Theoretical Computer Science, Elsevier,
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Amsterdam, 1990. Also in Carl Pomerance's lecture notes on Cryptology and
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Computational Number Theory, 1990.
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* New function: mpq_get_ifstr (int_str, frac_str, base,
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precision_in_som_way, rational_number). Convert RATIONAL_NUMBER to a
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string in BASE and put the integer part in INT_STR and the fraction part
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in FRAC_STR. (This function would do a division of the numerator and the
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denominator.)
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* Should mpz_powm* handle negative exponents?
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* udiv_qrnnd: If the denominator is normalized, the n0 argument has very
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little effect on the quotient. Maybe we can assume it is 0, and
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compensate at a later stage?
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* Better sqrt: First calculate the reciprocal square root, then multiply by
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the operand to get the square root. The reciprocal square root can be
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obtained through Newton-Raphson without division. The iteration is x :=
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x*(3-a*x^2)/2, where a is the operand.
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* Newton-Raphson using multiplication: We get twice as many correct digits
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in each iteration. So if we square x(k) as part of the iteration, the
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result will have the leading digits in common with the entire result from
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iteration k-1. A _mpn_mul_lowpart could implement this.
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* Peter Montgomery: If 0 <= a, b < p < 2^31 and I want a modular product
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a*b modulo p and the long long type is unavailable, then I can write
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typedef signed long slong;
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typedef unsigned long ulong;
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slong a, b, p, quot, rem;
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quot = (slong) (0.5 + (double)a * (double)b / (double)p);
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rem = (slong)((ulong)a * (ulong)b - (ulong)p * (ulong)q);
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if (rem < 0} {rem += p; quot--;}
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FFT:
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{
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* Multiplication could be done with Montgomery's method combined with
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the "three primes" method described in Lipson. Maybe this would be
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faster than to Nussbaumer's method with 3 (simple) moduli?
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* Maybe the modular tricks below are not needed: We are using very
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special numbers, Fermat numbers with a small base and a large exponent,
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and maybe it's possible to just subtract and add?
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* Modify Nussbaumer's convolution algorithm, to use 3 words for each
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coefficient, calculating in 3 relatively prime moduli (e.g.
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0xffffffff, 0x100000000, and 0x7fff on a 32-bit computer). Both all
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operations and CRR would be very fast with such numbers.
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* Optimize the Shoenhage-Stassen multiplication algorithm. Take
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advantage of the real valued input to save half of the operations and
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half of the memory. Try recursive variants with large, optimized base
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cases. Use recursive FFT with large base cases, since recursive FFT
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has better memory locality. A normal FFT get 100% cache miss.
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}
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* Speed modulo arithmetic, using Montgomery's method or my pre-invertion
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method. In either case, special arithmetic calls would be needed,
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mpz_mmmul, mpz_mmadd, mpz_mmsub, plus some kind of initialization
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functions.
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* mpz_powm* should not use division to reduce the result in the loop, but
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instead pre-compute the reciprocal of the MOD argument and do reduced_val
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= val-val*reciprocal(MOD)*MOD, or use Montgomery's method.
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* mpz_mod_2expplussi -- to reduce a bignum modulo (2**n)+s
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* It would be a quite important feature never to allocate more memory than
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really necessary for a result. Sometimes we can achieve this cheaply, by
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deferring reallocation until the result size is known.
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* New macro in longlong.h: shift_rhl that extracts a word by shifting two
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words as a unit. (Supported by i386, i860, HP-PA, RS6000, 29k.) Useful
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for shifting multiple precision numbers.
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* The installation procedure should make a test run of multiplication to
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decide the threshold values for algorithm switching between the available
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methods.
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* The gcd algorithm could probably be improved with a divide-and-conquer
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(DAC) approach. At least the bulk of the operations should be done with
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single precision.
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* Fast output conversion of x to base B:
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1. Find n, such that (B^n > x).
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2. Set y to (x*2^m)/(B^n), where m large enough to make 2^n ~~ B^n
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3. Multiply the low half of y by B^(n/2), and recursively convert the
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result. Truncate the low half of y and convert that recursively.
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Complexity: O(M(n)log(n))+O(D(n))!
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* Extensions for floating-point arithmetic.
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* Improve special cases for division.
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1. When the divisor is just one word, normalization is not needed for
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most CPUs, and can be done in the division loop for CPUs that need
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normalization.
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2. Even when the result is going to be very small, (i.e. nsize-dsize is
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small) normalization should also be done in the division loop.
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To fix this, a new routine mpn_div_unnormalized is needed.
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* Never allocate temporary space for a source param that overlaps with a
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destination param needing reallocation. Instead malloc a new block for
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the destination (and free the source before returning to the caller).
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* When any of the source operands overlap with the destination, mult (and
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other routines) slow down. This is so because the need of temporary
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allocation (with alloca) and copying. If a new destination were
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malloc'ed instead (and the overlapping source free'd before return) no
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copying would be needed. Is GNU malloc quick enough to make this faster
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even for reasonably small operands?
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Local Variables:
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mode: text
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fill-column: 75
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version-control: never
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End:
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