Does a large amount of GPU memory help when working with very large images and image mosaics?
Esri has released ArcGIS Pro, which makes use of the GPU for rendering and some processing:
- Graphics adapter resources
In ArcGIS Pro, the graphics engine limits drawing based on the abilities of your graphics processing unit (GPU).
- GPU processing with Spatial Analyst
Spatial Analyst now offers enhanced performance with the use of Graphics Processing Unit (GPU) processing for some tools. This technology takes advantage of the computing power of the graphics card in modern computers to improve the performance of certain operations.
The only GIS that utilize GPU power for processing data is called MapD. Harvard Tweetmap data are processed through this software.
Harvard Tweetmap Powered by MapD
MapD Project -- Massive Spatial Data Computing
Another way is to install ArcGIS background processing for 64-bit processor.
That will absolutely decrease the raster image calculation time as they are all in the background process.
ArcGIS Background Geoprocessing
For image processing, there are currently two projects that deal with this:
- GIS Tools for Hadoop
Those projects are dealing directly with parallel systems (as GPU processing and High Performance Computing), but not limited to it , and being able to implement on distributed systems. GIS Tools for Hadoop was initially designed to work on a Hadoop environment, but now they are movimg to Spark. Geotrellis was directly involved with Spark.
One issue to consider when dealing with parallel/distributed computing on image processing/remote sensing, is that the majority of algorithms have implementation that serializes the data while processing, so the big effort on projects nowadays is moving those legacy algorithms to work on distrubuted data structures, which is quite challenging.