update docs to include information in joss paper

Author: jonahm-LANL

doc/sphinx/index.rst

@@ -24,6 +24,12 @@ slice shown) on a GPU, with second-order convergence:
 
 .. image:: ../../figs/convergence.png
 
+Interpolation is fast and portable. Here's a benchmark showing
+performance on CPU and GPU for several architectures and problem
+sizes:
+
+.. image:: ../../figs/spiner_interpolation_benchmark.png
+
 See below for details of how to use spiner in your project and how to
 develop for it.
 
@@ -42,6 +48,7 @@ automatically integrated into the build system.
    :maxdepth: 1
    :caption: Contents:
 
+   src/statement-of-need
    src/building
    src/getting-started
    src/databox

doc/sphinx/src/statement-of-need.rst

@@ -0,0 +1,71 @@
+.. _statement-of-need:
+
+Why Develop Spiner?
+====================
+
+As Moore's law comes to an end, more and more performance comes from
+specialized hardware, such as GPUs. A key tool in the toolbox for many
+scientific codes is tabulated data. Fluid and continuum dynamics codes
+often encapsulate the equation of state as data tabulated in density
+and temperature. Radiation transport uses emissivity and
+absorption opacity on tables such as those computed in
+[@SullivanWeak]. As continuum dynamics is required for a variety of
+applications, such as astrophysics, geophysics, climate science,
+vehicle engineering, and national security, utilizing a very large
+number of supercomputer cycles, providing tabulated data for these
+applications has the potential for significant impact.
+
+These capabilities must be supported on all hardware a code may be run
+on, whether this is an NVIDIA GPU, an Intel CPU, or a next generation
+accelerator manufactured by one of any number of hardware vendors. To
+our knowledge there is no performance portable interpolation library
+on which these codes can rely, and there is a clear need, which we
+have developed ``Spiner`` to meet.
+
+To see some examples of software projects that leverage ``Spiner`` see
+`singularity-EOS`_, `singularity-opac`_, and `Phoebus`_.
+
+.. _singularity-eos: https://github.com/lanl/singularity-eos
+
+.. _singularity-opac: https://github.com/lanl/singularity-eos
+
+.. _Phoebus: https://github.com/lanl/singularity-opac
+
+State of the Field
+^^^^^^^^^^^^^^^^^^^
+
+Interpolation is a common problem, implemented countless times across
+software projects, and a core part of any introductory text on
+scientific computing. In graphics applications interpolation is so
+ubiquitous that hardware primitives are provided by GPUs. These
+hardware intrinsics are, however, severely limited for scientific
+application. For example, on NVIDIA GPUs, the values to be
+interpolated must be single precision floating point, and the
+interpolation coefficients themselves are only half-precision, which
+is often insufficient to capture the high precision required for
+scientific applications. As GPUs are inherently vector devices,
+hardware interpoaltion is also vectorized in nature. However,
+downstream applications may be easier to reason about if scalar
+operations are available. For example, equation of state lookups often
+require root finds on interpolated data, and this can be easier to
+implement as a scalar operation, even if the final operation is
+vectorized over warps. Texture interpolation also does not support
+multi-dimensional mixed indexing/interpoaltion operations where, say,
+three indices of a four-dimensional array are interpolated and one is
+merely indexed into.
+
+Moreover, relying on hardware intrinsics is not a portable solution. A
+software interpolation library can, if written with care, work on not
+only the current generation of accelerators, but also on general
+purpose CPUs and the next generation of hardware as well.
+
+Unfortunately, a performance-portable implementation not tuned to a
+specific use-case or embedded in a larger project is (to our
+knowledge) not available in the literature. A common problem in
+performance-portable computing is the management of
+performance-portable data structures.
+
+Interpolation is far more ubiquitous than its application in continuum
+dynamics and radiation transport, and we expect Spiner will find
+applications in the broader space of applications, such as image
+resampling. However, the team built Spiner with simulations in mind.