Spatio-Temporal Parallelism

ParaView Spatio-Temporal Parallel Processing Tools

Intended Audience and Purpose

The ParaView Spatio-Temporal Parallel Processing Tools are designed to dramatically reduce the running time of parallel data analysis jobs under certain conditions. These conditions include:

1. . The data is composed of a large amount of time steps.
2. . The data analysis operations are to be applied to each time step, and time steps are independent of each other (i.e. no data exchange between time steps is required). Examples Include generating an image of each time step and creating a contour of each time step.
3. . Optionally, for spatial parallelism the data for a single time step does not fit in a single core’s available memory while utilizing all cores on the processor or node.

Introduction and problem definition

In the age of “big data”, dealing with the massive amount of data can be an enormous challenge. For our definition of big data with respect to scientific computing, we are going by the working definition of data that requires an inordinate amount of time to analyze to obtain salient information on an appropriate computing platform. Often when the analysis is separate from the computation (i.e. the simulation code producing the data), disk IO can be a significant factor. According to the DOE Exascale Initiative Roadmap, Architecture and Technology Workshop in San Diego in December 2009, for supercomputers there is expected to be a 500 fold increase in the FLOP/s between 2010 and 2018 but only a 100 fold increase in the IO bandwidth in that same time. Because of this we need to concentrate on ways to efficiently post-process simulation data generated on these leading edge supercomputers.

Approach and solutions

To this end we have approached this problem by reducing the amount of global operations that need to be done to process the data. We begin with the assumption that the simulation is time dependent and will be outputting data for multiple time steps. When processing this data, similar operations will need to be done for each time step but we look to group the amount of processes that work on a time step together to a reasonable size instead of using all of the available processes. We call the set of processes working together on a time step as the time compartment. By having multiple time compartments we can ensure that there is an appropriate amount of work being done by each process. Additionally, the communication between processes is generally done within the time compartment and not over the entire global set of processes. In fact, for certain situations such as creating an image for each time step there will be no global inter-process communication. An example of this is shown in the figure below for 3 time steps and 3 time compartments of size 4. Note that for more time steps each time compartment would process multiple time steps for this example.