Developer Reference

  • 2021.1
  • 12/04/2020
  • Public Content
Contents

Vector Arguments in Vector Math

Vector arguments of classic VM mathematical functions are passed in one-dimensional arrays with unit vector increment. It means that a vector of length
n
is passed contiguously in an array
a
whose values are defined as
a[0], a[1], ..., a[
n
-1]
.
Strided VM mathematical functions allow using positive increments for all input and output vector arguments.
To accommodate for arrays with other increments, or more complicated indexing, VM contains auxiliary Pack/Unpack functions that gather the array elements into a contiguous vector and then scatter them after the computation is complete.
Generally, if the vector elements are stored in a one-dimensional array
a
as
a[m0], a[m1], ..., a[mn-1]
and need to be regrouped into an array
y
as
y[k0], y[k1], ..., y[kn-1],
.
VM Pack/Unpack functions can use one of the following indexing methods:

Positive Increment Indexing

kj = incy * j, mj = inca * j, j = 0 ,..., n-1
.
Constraint:
incy > 0
and
inca > 0
.
For example, setting incy = 1 specifies gathering array elements into a contiguous vector.
This method is similar to that used in BLAS, with the exception that negative and zero increments are not permitted.

Index Vector Indexing

.
kj = iy[j], mj = ia[j], j = 0 ,..., n-1
.
where ia and iy are arrays of length
n
that contain index vectors for the input and output arrays
a
and
y
, respectively.

Mask Vector Indexing

Indices
kj
,
mj
are such that:
.
my[kj] 
 0, ma[mj] 
 0 , j = 0,..., n-1
.
where
ma
and
my
are arrays that contain mask vectors for the input and output arrays
a
and
y
, respectively.

Product and Performance Information

1

Performance varies by use, configuration and other factors. Learn more at www.Intel.com/PerformanceIndex.