StarPU Handbook
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Here is a list of all modules:
oBitmapThis section describes the bitmap facilities provided by StarPU
oCodelet And TasksThis section describes the interface to manipulate codelets and tasks
oCUDA Extensions
oData Interfaces
oData ManagementThis section describes the data management facilities provided by StarPU. We show how to use existing data interfaces in Data Interfaces, but developers can design their own data interfaces if required
oOut Of Core
oData Partition
oExpert Mode
oExplicit Dependencies
oFFT Support
oFxT Support
oImplicit Data DependenciesIn this section, we describe how StarPU makes it possible to insert implicit task dependencies in order to enforce sequential data consistency. When this data consistency is enabled on a specific data handle, any data access will appear as sequentially consistent from the application. For instance, if the application submits two tasks that access the same piece of data in read-only mode, and then a third task that access it in write mode, dependencies will be added between the two first tasks and the third one. Implicit data dependencies are also inserted in the case of data accesses from the application
oInitialization and Termination
oTheoretical Lower Bound on Execution TimeCompute theoretical upper computation efficiency bound corresponding to some actual execution
oMIC Extensions
oMiscellaneous Helpers
oModularized Scheduler Interface
oMPI Support
oMultiformat Data Interface
oOpenCL Extensions
oOpenMP Runtime SupportThis section describes the interface provided for implementing OpenMP runtimes on top of StarPU
oParallel Tasks
oPerformance Model
oRunning Drivers
oSCC Extensions
oScheduling ContextsStarPU permits on one hand grouping workers in combined workers in order to execute a parallel task and on the other hand grouping tasks in bundles that will be executed by a single specified worker. In contrast when we group workers in scheduling contexts we submit starpu tasks to them and we schedule them with the policy assigned to the context. Scheduling contexts can be created, deleted and modified dynamically
oScheduling PolicyTODO. While StarPU comes with a variety of scheduling policies (see Task Scheduling Policy), it may sometimes be desirable to implement custom policies to address specific problems. The API described below allows users to write their own scheduling policy
oStandard Memory Library
oTask Bundles
oTask Lists
oThreadsThis section describes the thread facilities provided by StarPU. The thread function are either implemented on top of the pthread library or the Simgrid library when the simulated performance mode is enabled (SimGrid Support)
oToolboxThe following macros allow to make GCC extensions portable, and to have a code which can be compiled with any C compiler
oStarPU-Top Interface
oTreeThis section describes the tree facilities provided by StarPU
oWorkers’ Properties
oScheduling Context Hypervisor - Building a new resizing policy
\Scheduling Context Hypervisor - Regular usage