1#!F-adobe-helvetica-medium-r-normal--18* 2#!N 3#!CNavyBlue #!N #!Rall272 4Parallelism for Data Explorer SMP #!N #!EC #!N #!N For completeness, 5the notion of module parallelism is discussed here. If you are 6developing visualizations or modules exclusively for use with the IBM Visualization 7Data Explorer running on a single-processor workstation, then these concepts are 8not applicable. However, if your visualizations or modules are to be 9run on both the IBM Visualization Data Explorer and IBM Visualization 10Data Explorer SMP, then these concepts are important for achieving higher 11performance. #!N #!N Every module that performs any significant amount of 12processing is "parallelized"; that is, the module makes use of all 13processors made available to Data Explorer to operate on the data. 14#!N #!N Data Explorer uses explicit data partitioning as the primary 15framework for parallelism. Data Explorer partitions the data into local, self-contained 16regions. In general, visualization modules then generate subtasks corresponding to partitions. 17For more information about partitioning, see Partition in IBM Visualization Data 18Explorer User's Reference. #!N #!N In general, parallel programming is complex. 19To help manage it, Data Explorer simplifies the process by providing 20a simple fork-join parallelism model to implement coarse-grain shared memory parallelization 21(data parallel). Using data partitions, read-only objects, and a single-fork join 22mode simplifies the module writing task by avoiding the explicit use 23of locks in modules, thereby reducing the possibility of deadlock. For 24information about adding modules to the Data Explorer system, see IBM 25Visualization Data Explorer Programmer's Reference. #!N #!N #!N #!F-adobe-times-medium-i-normal--18* Next Topic 26#!EF #!N #!N #!Lunduse,dxall274 h Graphical User Interface: Basics #!EL #!N #!F-adobe-times-medium-i-normal--18* #!N 27