[GRASS-dev] [SoC] Parallelization of Raster and Vector libraries

[Glynn Clements]

Jordan Neumeyer wrote:

> > > Just kind of my thought process about how I would try to go about
> > > parallelizing a module.
> >
> > The main issue with parallelising raster input is that the library
> > keeps a copy of the current row's data, so that consecutive reads of
> > the same row (as happen when upsampling) don't re-read the data.
> >
> > For concurrent access to a single map, you would need to either keep
> > one row per thread, or abandon caching. Also, you would need to use
> > pread() rather than fseek()+read().
> 
> It sounds like you're talking about parallelism in I/O from a file or
> database. Neither of which is my intent or goal for this project. I will
> parallelize things after they have already been read into memory, and tasks
> are processor intensive. I wouldn't want parallelize any I/O, but if I were
> to optimize I/O. I would make all operations I/O asynchronous, which is can
> mimic parallelism in a sense. Queuing up the chunks of data and then
> processing them as resources become available.

Most GRASS raster modules process data row-by-row, rather than reading
entire maps into memory. Reading maps into memory is frowned upon, as
GRASS is regularly used with maps which are too large to fit into
memory. Where the algorithm cannot operate row-by-row, use of a tile
cache is the next best alternative; see e.g. r.proj.seg (renamed to
r.proj in 7.0).

Holding an entire map in memory is only considered acceptable if the
algorithm is inherently so slow that processing a gigabyte-sized map
simply wouldn't be feasible, or the access pattern is such that even a
tile-cache approach isn't feasible.

In general, GRASS should be able to process multi-gigabyte maps even
on 32-bit systems, and work on multi-user systems where a process
cannot assume that it can use a significant proportion of the system's
total physical memory.

> > It's more straightfoward to read multiple maps concurrently. In 7.0,
> > this case should be thread-safe.
> >
> > Alternatively, you could have one thread for reading, one for writing,
> > and multiple worker threads for the actual processing. However, unless
> > the processing is complex, I/O will be the bottleneck.
> >
> 
> I/O is generally a bottleneck anyway. Something always tends to be waiting
> on another.

When I refer to I/O, I'm referring not just to read() and write(), but
also the (de)compression, conversion and resampling, i.e. everything
performed by the get/put-row functions. For many GRASS modules, this
takes more time than the actual processing.

Finally, the thread title refers to libraries. Very little processing
occurs in the libraries; most of it is in the individual modules. So
there isn't much scope for "parallelising" the libraries. The main
issue for library functions is to ensure that they are thread-safe. 
Most of the necessary work for the raster library has been done in
7.0.

-- 
Glynn Clements <glynn at gclements.plus.com>