An Always Correct Method

نویسندگان

  • Marc Andrysco
  • Ranjit Jhala
  • Sorin Lerner
چکیده

Floating-point numbers are an essential part of modern software, recently gaining particular prominence on the web as the exclusive numeric format of Javascript. To use floating-point numbers, we require a way to convert binary machine representations into human readable decimal outputs. Existing conversion algorithms make trade-offs between completeness and performance. The classic Dragon4 algorithm by Steele and White and its later refinements achieve completeness — i.e. produce correct and optimal outputs on all inputs — by using arbitrary precision integer (bignum) arithmetic which leads to a high performance cost. On the other hand, the recent Grisu3 algorithm by Loitsch shows how to recover performance by using native integer arithmetic but sacrifices optimality for 0.5% of all inputs. We present Errol, a new complete algorithm that is guaranteed to produce correct and optimal results for all inputs by sacrificing a speed penalty of 2.4× to the incomplete Grisu3 but 5.2× faster than previous complete methods.

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تاریخ انتشار 2016