AnimationLoopParallelScheduler
The `AnimationLoopParallelScheduler` is part of SOFA's MultiThreading module and serves as a parallel animation loop, leveraging the Intel tbb (Thread Building Blocks) library for efficient multithreaded execution. This component inherits from both `BaseAnimationLoop` and `TaskSchedulerUser`, integrating seamlessly into SOFA's simulation framework to manage concurrent processing during simulation steps. The role of this component is to enable parallel execution of tasks within the simulation loop, thereby improving performance by utilizing multiple threads for computationally intensive operations typical in medical simulations. The primary interactions occur through inherited methods from `BaseAnimationLoop`, such as `init()`, `bwdInit()`, `reinit()`, `cleanup()`, and `step()` which manage initialization, cleanup, reinitialization, and per-step processing, respectively. In practical usage, this component is typically initialized with a simulation node (`sofa::simulation::Node`). The `init` method sets up the task scheduler required for parallel execution. Methods like `bwdInit`, `reinit`, and `cleanup` are used to manage lifecycle events specific to multithreading contexts, ensuring proper setup and tear-down of thread-related resources. The `step` method performs parallel processing by dividing tasks among threads, using SOFA's task scheduler framework (`TaskScheduler`). This enables efficient handling of simulation steps where multiple nodes can be processed concurrently. The component does not expose any additional data fields beyond what is inherited from its base classes.
- abstract
- The `AnimationLoopParallelScheduler` manages parallel execution of tasks within SOFA's simulation loop using Intel tbb for multithreaded processing.
- sheet
- # AnimationLoopParallelScheduler **Overview:** The `AnimationLoopParallelScheduler` is a component in the MultiThreading module that enables parallel execution of tasks during the simulation loop. It inherits from `BaseAnimationLoop` and `TaskSchedulerUser`, providing methods for initialization (`init()`), backward initialization (`bwdInit()`), reinitialization (`reinit()`), cleanup (`cleanup()`), and per-step processing (`step()`). This component leverages Intel tbb to manage concurrent tasks efficiently. **Practical Notes:** The `AnimationLoopParallelScheduler` is designed for simulations that require high performance through multithreading. Proper configuration of the task scheduler is crucial for optimal parallel execution, and users should ensure that thread-related resources are managed correctly during initialization and cleanup phases.
- description
- The `AnimationLoopParallelScheduler` is part of SOFA's MultiThreading module and serves as a parallel animation loop, leveraging the Intel tbb (Thread Building Blocks) library for efficient multithreaded execution. This component inherits from both `BaseAnimationLoop` and `TaskSchedulerUser`, integrating seamlessly into SOFA's simulation framework to manage concurrent processing during simulation steps. The role of this component is to enable parallel execution of tasks within the simulation loop, thereby improving performance by utilizing multiple threads for computationally intensive operations typical in medical simulations. The primary interactions occur through inherited methods from `BaseAnimationLoop`, such as `init()`, `bwdInit()`, `reinit()`, `cleanup()`, and `step()` which manage initialization, cleanup, reinitialization, and per-step processing, respectively. In practical usage, this component is typically initialized with a simulation node (`sofa::simulation::Node`). The `init` method sets up the task scheduler required for parallel execution. Methods like `bwdInit`, `reinit`, and `cleanup` are used to manage lifecycle events specific to multithreading contexts, ensuring proper setup and tear-down of thread-related resources. The `step` method performs parallel processing by dividing tasks among threads, using SOFA's task scheduler framework (`TaskScheduler`). This enables efficient handling of simulation steps where multiple nodes can be processed concurrently. The component does not expose any additional data fields beyond what is inherited from its base classes.
- math_and_phys_description
- The `AnimationLoopParallelScheduler` component in SOFA's MultiThreading module serves to manage the parallel execution of tasks within the simulation loop using the Intel TBB library, without directly interacting with any specific mathematical or physical models intrinsic to medical simulations. This component primarily focuses on the computational aspects and does not involve equations or physical principles that govern the behavior of objects or systems in a simulation. Its role is to ensure efficient utilization of multiple threads for tasks such as initialization (`init`), reinitialization (`reinit`), cleanup (`cleanup`), backward initialization (`bwdInit`), and per-step processing (`step`). These methods are part of the inherited `BaseAnimationLoop` interface, and the component leverages SOFA's task scheduler to distribute workloads efficiently across multiple threads. The component does not provide additional data fields or physical parameters beyond those inherited from its base classes.
{
"name": "AnimationLoopParallelScheduler",
"main": {
"name": "AnimationLoopParallelScheduler",
"namespace": "multithreading::component::animationloop",
"module": "MultiThreading",
"include": "MultiThreading/component/animationloop/AnimationLoopParallelScheduler.h",
"doc": "Parallel animation loop, using the Intel tbb library.",
"inherits": [
"BaseAnimationLoop",
"TaskSchedulerUser"
],
"templates": [],
"data_fields": [],
"links": [],
"methods": [
{
"name": "init",
"return_type": "void",
"params": [],
"is_virtual": true,
"is_pure_virtual": false,
"is_static": false,
"access": "public"
},
{
"name": "bwdInit",
"return_type": "void",
"params": [],
"is_virtual": true,
"is_pure_virtual": false,
"is_static": false,
"access": "public"
},
{
"name": "reinit",
"return_type": "void",
"params": [],
"is_virtual": true,
"is_pure_virtual": false,
"is_static": false,
"access": "public"
},
{
"name": "cleanup",
"return_type": "void",
"params": [],
"is_virtual": true,
"is_pure_virtual": false,
"is_static": false,
"access": "public"
},
{
"name": "step",
"return_type": "void",
"params": [
{
"name": "params",
"type": "const sofa::core::ExecParams *"
},
{
"name": "dt",
"type": "SReal"
}
],
"is_virtual": true,
"is_pure_virtual": false,
"is_static": false,
"access": "public"
}
]
},
"desc": {
"description": "The `AnimationLoopParallelScheduler` is part of SOFA's MultiThreading module and serves as a parallel animation loop, leveraging the Intel tbb (Thread Building Blocks) library for efficient multithreaded execution. This component inherits from both `BaseAnimationLoop` and `TaskSchedulerUser`, integrating seamlessly into SOFA's simulation framework to manage concurrent processing during simulation steps.\n\nThe role of this component is to enable parallel execution of tasks within the simulation loop, thereby improving performance by utilizing multiple threads for computationally intensive operations typical in medical simulations. The primary interactions occur through inherited methods from `BaseAnimationLoop`, such as `init()`, `bwdInit()`, `reinit()`, `cleanup()`, and `step()` which manage initialization, cleanup, reinitialization, and per-step processing, respectively.\n\nIn practical usage, this component is typically initialized with a simulation node (`sofa::simulation::Node`). The `init` method sets up the task scheduler required for parallel execution. Methods like `bwdInit`, `reinit`, and `cleanup` are used to manage lifecycle events specific to multithreading contexts, ensuring proper setup and tear-down of thread-related resources.\n\nThe `step` method performs parallel processing by dividing tasks among threads, using SOFA's task scheduler framework (`TaskScheduler`). This enables efficient handling of simulation steps where multiple nodes can be processed concurrently. The component does not expose any additional data fields beyond what is inherited from its base classes."
},
"maths": {
"math_and_phys_description": "The `AnimationLoopParallelScheduler` component in SOFA's MultiThreading module serves to manage the parallel execution of tasks within the simulation loop using the Intel TBB library, without directly interacting with any specific mathematical or physical models intrinsic to medical simulations. This component primarily focuses on the computational aspects and does not involve equations or physical principles that govern the behavior of objects or systems in a simulation. Its role is to ensure efficient utilization of multiple threads for tasks such as initialization (`init`), reinitialization (`reinit`), cleanup (`cleanup`), backward initialization (`bwdInit`), and per-step processing (`step`). These methods are part of the inherited `BaseAnimationLoop` interface, and the component leverages SOFA's task scheduler to distribute workloads efficiently across multiple threads. The component does not provide additional data fields or physical parameters beyond those inherited from its base classes."
},
"summary": {
"abstract": "The `AnimationLoopParallelScheduler` manages parallel execution of tasks within SOFA's simulation loop using Intel tbb for multithreaded processing.",
"sheet": "# AnimationLoopParallelScheduler\n\n**Overview:**\nThe `AnimationLoopParallelScheduler` is a component in the MultiThreading module that enables parallel execution of tasks during the simulation loop. It inherits from `BaseAnimationLoop` and `TaskSchedulerUser`, providing methods for initialization (`init()`), backward initialization (`bwdInit()`), reinitialization (`reinit()`), cleanup (`cleanup()`), and per-step processing (`step()`). This component leverages Intel tbb to manage concurrent tasks efficiently.\n\n**Practical Notes:**\nThe `AnimationLoopParallelScheduler` is designed for simulations that require high performance through multithreading. Proper configuration of the task scheduler is crucial for optimal parallel execution, and users should ensure that thread-related resources are managed correctly during initialization and cleanup phases."
}
}