chop
is a MATLAB function for rounding the elements of a matrix to a
lower precision arithmetic with one of several forms of rounding. Its
intended use is for simulating arithmetic of different precisions (less
than double) with various rounding modes. The input to chop
should be
single precision or double precision and the output will have the same
type: the lower precision numbers are stored within a higher precision type.
The arithmetic formats supported are
- 'b', 'bfloat16' - bfloat16,
- 'h', 'half', 'fp16' - IEEE half precision (the default),
- 's', 'single', 'fp32' - IEEE single precision,
- 'd', 'double', 'fp64' - IEEE double precision,
- 'c', 'custom' - custom format.
Subnormal numbers can be supported or not, and in the latter case they are flushed to zero.
Several rounding modes are supported:
- Round to nearest using round to even last bit to break ties (the default).
- Round towards plus infinity (round up).
- Round towards minus infinity (round down).
- Round towards zero.
- Stochastic rounding - round to the next larger or next smaller floating-point number with probability proportional to the distance to those floating-point numbers.
- Stochastic rounding - round to the next larger or next smaller floating-point number with equal probability.
A further option causes each element of the rounded result to have, with a specified probability defaulting to 0.5, a randomly chosen bit in its significand flipped.
Demonstration function:
demo-harmonic
computes the harmonic series in several arithmetic formats using all the supported rounding modes.
Other M-file:
roundit
is a function for rounding a matrix to have integer entries. It is used bychop
and is not intended to be called directly.
Test functions:
test_chop
is a test function forchop
.test_roundit
is a test function forroundit
.
Each test function should print "All tests successful!".
The function chop
is a successor to a function of the same name in the
The Matrix Computation Toolbox
(also available on
File Exchange).
The code was developed in MATLAB R2018b and works with versions at least back to R2016a.
Nicholas J. Higham and Srikara Pranesh, Simulating Low Precision Floating-Point Arithmetic, MIMS Eprint 2019.4, Manchester Institute for Mathematical Sciences, The University of Manchester, UK, March 2019.
See license.txt
for licensing information.