Comment by Matthew Mccormick
In this article, the authors summarize challenges related to parallelism
in modern high performance computing and present improvements to the Insight
Toolkit (ITK) with Threading Building Blocks (TBB).

The hypothesis is that threads in many-core CPUs are starved for work given
the way that data is divided and distributed among threads. A more
fine-grained and dynamic data decomposition and improved job scheduling will
improve performance.

The authors provide source code, data, and bash scripts for a quality,
reproducible open science publication. Proposed improvements to ITK image
processing filters with TBB are described, and evidence for the improvements
are provided with example, realistic DWI processing.

Overall, this is an excellent publication that describes the high performance
computing challenges in ITK well and touches on an appropriate solution with
TBB. While the hypothesis that performance gains are likely partially related
to idle threads as proposed, much of the performance gains are also likely due
to reduce overhead from spawning and destroying threads. This work has the
potential to be very high impact. The improvements to a very large number of
algorithms available in ITK are significant. While the benchmarking performed
was on a 12-core Xeon system, which is a common system today, systems are coming
available, like the Knight's Landing Phi processor, which will experience
even greater performance improvements.

The following improvements and next steps will ensure this work is high
impact:

The main code should be submitted to the Gerrit code review system, and
improvements should be made to ensure it works on all supported platforms,
follows ITK style guidelines, etc. This process is described here:

https://itk.org/ITKSoftwareGuide/html/Book1/ITKSoftwareGuide-Book1ch10.html


In practice, it is not possible to have a hard dependency on TBB for ITK. TBB
cannot be bundled with ITK because of its size, its license, and its build
system. It can be difficult to obtain and configure against. It does not
support all platforms that people use with ITK. So, the addition should be an
optional ITK configuration setting enabled with CMake.

Since it is not practical to maintain two duplicate version of all filters,
the proposed code should be added to itk::ImageSource when TBB is available
which will not require duplication or modification of existing filters.

It may be possible for existing filters to re-use their
ThreadedGenerateData method by passing the tbb::block_range::begin() value as a
substitute for the ThreadIdType argument. While this is not the thread id, it
may fulfill the needs of how many filters, which currently use the
argument to conditionally performing operations when its value is 0, perform
progress reporting, etc. An optional specialized TBB method could be
implemented by filters and used when available.

In terms of data division, another improvement would implement the proposed
strategy as an implementation of the itk::ImageRegionSplitterBase or
itk::ThreadedDomainPartitioner class, and set this new class as the default when TBB
is enabled. This will make it possible to override the strategy with other
implementations in the future.