cpp-taskflow/cpp-taskflow
Cpp Taskflow
Cpp-taskflow is a C++ task-parallelism framework and task graph scheduler designed to manage and execute complex dependency graphs of parallel tasks across CPU and GPU hardware. It provides a parallel algorithm library for high-performance implementations of reductions, sorts, pipelines, and iterations.
The framework distinguishes itself through its ability to offload heavy computational workloads from a task graph to graphics processors for acceleration. It also includes a task profiling tool and a performance analysis interface for visualizing task execution flow and dependency structures to identify bottlenecks.
The library covers a broad range of parallel computing capabilities, including the orchestration of modular graph compositions and recursive subflows. It supports diverse execution patterns such as asynchronous task launching and conditional tasking to manage real-time control-flow decisions within a workflow.
Features
- C++ Task Engines - Provides a high-performance C++ framework for composing asynchronous tasks and GPU-offloaded workloads into parallel graphs.
- Execution Graphs - Provides a framework for constructing and managing directed acyclic graphs to execute interdependent tasks in parallel.
- Heterogeneous Workflow Orchestrators - Integrates hardware-accelerated GPU kernels into unified parallel execution pipelines via a specialized runtime.
- Task Schedulers - Features a task scheduler that manages execution order and dependencies to maximize core utilization and throughput.
- GPU Acceleration Libraries - Provides libraries for offloading intensive scientific computations from the C++ execution graph to the GPU.
- Headless GPU Compute Engines - Accelerates scientific workloads by executing general-purpose parallel calculations on the GPU without a display window.
- High-Performance Computing - Implements high-performance parallel algorithms such as reductions and sorts for efficient processing of large datasets.
- Parallel Algorithms - Ships a library of fundamental data-parallel operations, including parallel reductions and sorts.
- Task Scheduling - Provides a scheduler that resolves complex task dependencies using directed acyclic graphs to maximize hardware utilization.
- Dependency-Aware Task Orchestration - Ensures tasks execute in parallel only after their required prerequisites in the dependency structure are complete.
- Recursive Parallel Patterns - Implements nested dependency structures within C++ workflows to handle recursive computations in parallel.
- Parallel Execution Profilers - Provides diagnostic tools to analyze the performance of task-based programs and optimize work distribution.
- Work-Stealing Schedulers - Implements work-stealing schedulers to dynamically balance computational tasks across available hardware threads.
- Lock-Free Atomic Containers - Utilizes lock-free atomic containers for task submission and retrieval to minimize synchronization overhead between worker threads.
- Conditional Branching - Implements logic for routing execution paths based on real-time control-flow decisions within the task graph.
- Recursive Subflow Generators - Supports the dynamic generation of nested sub-graphs to handle recursive parallel workloads within a task flow.
- Execution Graph Compositions - Implements modular graph compositions that allow pre-defined task blocks to be combined into larger, reusable workflows.
- Parallel Task Spawning - Supports spawning multiple concurrent operations independently of the main graph to explore runtime parallelism.
- Task Dependency Visualizers - Includes utilities for exporting and inspecting task graph structures to debug execution flows and identify bottlenecks.
- Concurrency Libraries - Library for parallel task programming and scheduling.
