StarPU Handbook
Here is a list of all modules:
 BitmapThis section describes the bitmap facilities provided by StarPU
 Clustering Machine
 Codelet And TasksThis section describes the interface to manipulate codelets and tasks
 CUDA Extensions
 Data Interfaces
 Data 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
 Out Of Core
 Data Partition
 Expert Mode
 Explicit Dependencies
 FFT Support
 FxT Support
 Implicit 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
 Initialization and Termination
 Task Insert Utility
 Interoperability SupportThis section describes the interface supplied by StarPU to interoperate with other runtime systems
 Theoretical Lower Bound on Execution TimeCompute theoretical upper computation efficiency bound corresponding to some actual execution
 MIC Extensions
 Miscellaneous Helpers
 Modularized Scheduler Interface
 MPI Support
 Multiformat Data Interface
 OpenCL Extensions
 OpenMP Runtime SupportThis section describes the interface provided for implementing OpenMP runtimes on top of StarPU
 Parallel Tasks
 Performance Model
 Running Drivers
 SCC Extensions
 Scheduling 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
 Scheduling PolicyTODO. While StarPU comes with a variety of scheduling policies (see Task Scheduling Policies), 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
 Standard Memory Library
 Task Bundles
 Task Lists
 ThreadsThis 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)
 ToolboxThe following macros allow to make GCC extensions portable, and to have a code which can be compiled with any C compiler
 StarPU-Top Interface
 TreeThis section describes the tree facilities provided by StarPU
 Workers’ Properties
 Scheduling Context Hypervisor - Building a new resizing policy
 Scheduling Context Hypervisor - Regular usage