Worst Cases for the Exponential Function in the IEEE 754r decimal64 Format

We searched for the worst cases for correct rounding of the exponential function in the IEEE 754r decimal64 format, and computed all the bad cases whose distance from a breakpoint (for all rounding modes) is less than $10^{-15}$,ulp, and we give the worst ones. In particular, the worst case for $|x| geq 3 imes 10^{-11}$ is $exp(9.407822313572878 imes 10^{-2}) = 1.098645682066338,5,0000000000000000,278ldots$. This work can be extended to other elementary functions in the decimal64 format and allows the design of reasonably fast routines that will evaluate these functions with correct rounding, at least in some domains

Algorithms and architectures for decimal transcendental function computation

Nowadays, there are many commercial demands for decimal floating-point (DFP) arithmetic operations such as financial analysis, tax calculation, currency conversion, Internet based applications, and e-commerce. This trend gives rise to further development on DFP arithmetic units which can perform accurate computations with exact decimal operands. Due to the significance of DFP arithmetic, the IEEE 754-2008 standard for floating-point arithmetic includes it in its specifications. The basic decimal arithmetic unit, such as decimal adder, subtracter, multiplier, divider or square-root unit, as a main part of a decimal microprocessor, is attracting more and more researchers' attentions. Recently, the decimal-encoded formats and DFP arithmetic units have been implemented in IBM's system z900, POWER6, and z10 microprocessors. Increasing chip densities and transistor count provide more room for designers to add more essential functions on application domains into upcoming microprocessors. Decimal transcendental functions, such as DFP logarithm, antilogarithm, exponential, reciprocal and trigonometric, etc, as useful arithmetic operations in many areas of science and engineering, has been specified as the recommended arithmetic in the IEEE 754-2008 standard. Thus, virtually all the computing systems that are compliant with the IEEE 754-2008 standard could include a DFP mathematical library providing transcendental function computation. Based on the development of basic decimal arithmetic units, more complex DFP transcendental arithmetic will be the next building blocks in microprocessors. In this dissertation, we researched and developed several new decimal algorithms and architectures for the DFP transcendental function computation. These designs are composed of several different methods: 1) the decimal transcendental function computation based on the table-based first-order polynomial approximation method; 2) DFP logarithmic and antilogarithmic converters based on the decimal digit-recurrence algorithm with selection by rounding; 3) a decimal reciprocal unit using the efficient table look-up based on Newton-Raphson iterations; and 4) a first radix-100 division unit based on the non-restoring algorithm with pre-scaling method. Most decimal algorithms and architectures for the DFP transcendental function computation developed in this dissertation have been the first attempt to analyze and implement the DFP transcendental arithmetic in order to achieve faithful results of DFP operands, specified in IEEE 754-2008. To help researchers evaluate the hardware performance of DFP transcendental arithmetic units, the proposed architectures based on the different methods are modeled, verified and synthesized using FPGAs or with CMOS standard cells libraries in ASIC. Some of implementation results are compared with those of the binary radix-16 logarithmic and exponential converters; recent developed high performance decimal CORDIC based architecture; and Intel's DFP transcendental function computation software library. The comparison results show that the proposed architectures have significant speed-up in contrast to the above designs in terms of the latency. The algorithms and architectures developed in this dissertation provide a useful starting point for future hardware-oriented DFP transcendental function computation researches

Proceedings of the 7th Conference on Real Numbers and Computers (RNC'7)

These are the proceedings of RNC7

Worst Cases for the Exponential Function in the IEEE 754r decimal64 Format

We searched for the worst cases for correct rounding of the exponential function in the IEEE 754r decimal64 format, and computed all the bad cases whose distance from a breakpoint (for all rounding modes) is less than 10 −15 ulp, and we give the worst ones. In particular, the worst case for |x | ≥ 3 × 10 −11 is exp(9.407822313572878 × 10 −2) = 1.098645682066338 5 0000000000000000 278.... This work can be extended to other elementary functions in the decimal64 format and allows the design of reasonably fast routines that will evaluate these functions with correct rounding, at least in some domains

Évaluation efficace de fonctions numériques - Outils et exemples

With computers, it is possible to evaluate some numerical functions such as f = exp, sin, arccos, etc. The purpose of this thesis is to study how these functions can be implemented. Depending on the target architecture (software or hardware, small or high accuracy required), different problems must be addressed, but the final goal is always to eventually obtain an implementation as efficient as possible. We first study with an example the problems that arise in the case when the precision is arbitrary. When, on the contrary, the precision is known in advance, the function f is often replaced by an approximation polynomial p. Such a polynomial can then be very efficiently evaluated. In practice, the coefficients of p must be representable on a given finite number of bits. We propose several algorithms (some of them are heuristic and others are rigorous) for finding very good approximation polynomials satisfying this constraint. Our results also apply in the case when the approximant is a rational fraction. Once p has been found, one must prove that the error |p-f| is not greater than a given bound. The particular form of the function p-f (subtraction between two very close functions) makes this property hard to rigorously prove. We propose an algorithm for overcoming this difficulty. All these algorithms have been integrated into a software tool called Sollya, developed during the thesis. In the beginning, it was created for making the implementation of functions easier. Now, it may be interesting for anyone who needs to perform numerical computations in a safe environment.Les systèmes informatiques permettent d'évaluer des fonctions numériques telles que f = exp, sin, arccos, etc. Cette thèse s'intéresse au processus d'implémentation de ces fonctions. Suivant la cible visée (logiciel ou matériel, faible ou grande précision), les problèmes qui se posent sont différents, mais l'objectif est toujours d'obtenir l'implémentation la plus efficace possible. Nous étudions d'abord, à travers un exemple, les problèmes qui se posent dans le cas où la précision est arbitraire. Lorsque, à l'inverse, la précision est connue d'avance, la fonction f est souvent remplacée par un polynôme d'approximation p. Un tel polynôme peut ensuite être évalué très efficacement en machine. En pratique, les coefficients de p doivent être représentables sur un nombre fini donné de bits. Nous proposons un ensemble d'algorithmes (certains sont heuristiques, d'autres rigoureux) pour trouver de très bons polynômes d'approximation répondant à cette contrainte. Ces résultats s'étendent au cas où la fonction d'approximation est une fraction rationnelle. Une fois p trouvé, il faut prouver que l'erreur |p-f| n'excède pas un certain seuil. La nature particulière de la fonction p-f (soustraction de deux fonctions très proches) rend cette propriété difficile à prouver rigoureusement. Nous proposons un algorithme capable de contourner cette difficulté. Tous ces algorithmes ont été intégrés au logiciel Sollya, développé pendant la thèse. À l'origine conçu pour faciliter l'implémentation de fonctions, ce logiciel s'adresse à présent à toute personne souhaitant faire des calculs numériques dans un cadre complètement fiable