Sign in
Author
|
Conference
|
Journal
|
Organization
|
Year
|
DOI
Look for results that meet for the following criteria:
since
equal to
before
between
and
Search in all fields of study
Limit my searches in the following fields of study
Agriculture Science
Arts & Humanities
Biology
Chemistry
Computer Science
Economics & Business
Engineering
Environmental Sciences
Geosciences
Material Science
Mathematics
Medicine
Physics
Social Science
Multidisciplinary
Keywords
(11)
Data Type
Estimation Error
Floating Point
Interval Arithmetic
Linear Approximation
Mental Model
Numerical Analysis
Numerical Computation
Physical Simulation
Programming Language
Upper Bound
Subscribe
Academic
Publications
Trustworthy Numerical Computation in Scala
Trustworthy Numerical Computation in Scala,10.1145/2076021.2048094,Sigplan Notices,Eva Darulov'a,Viktor Kuncak
Edit
Trustworthy Numerical Computation in Scala
BibTex
|
RIS
|
RefWorks
Download
Eva Darulov'a
,
Viktor Kuncak
Modern computing has adopted the
floating point
type as a default way to describe computations with real numbers. Thanks to dedicated hardware support, such computations are efficient on modern architectures, even in double precision. However, rigorous reasoning about the resulting programs remains difficult. This is in part due to a large gap between the finite
floating point
representation and the infinite-precision real-number semantics that serves as the developers' mental model. Because programming languages do not provide support for estimating errors, some computations in practice are performed more and some less precisely than needed. We present a library solution for rigorous arithmetic computation. Our numerical
data type
library tracks a (double)
floating point
value, but also a guaranteed
upper bound
on the error between this value and the ideal value that would be computed in the real-value semantics. Our implementation involves a set of linear approximations based on an extension of affine arithmetic. The derived approximations cover most of the standard mathematical operations, including trigonometric functions, and are more comprehensive than any publicly available ones. Moreover, while
interval arithmetic
rapidly yields overly pessimistic estimates, our approach remains precise for several computational tasks of interest. We evaluate the library on a number of examples from
numerical analysis
and physical simulations. We found it to be a useful tool for gaining confidence in the correctness of the computation.
Journal:
Sigplan Notices - SIGPLAN
, pp. 325-344, 2011
DOI:
10.1145/2076021.2048094
Cumulative
Annual
View Publication
The following links allow you to view full publications. These links are maintained by other sources not affiliated with Microsoft Academic Search.
(
dl.acm.org
)