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