This page collects self-contained examples that demonstrate Taskflow across a broad range of parallel programming patterns, from classic graph algorithms and numerical computing to dynamic task graphs, async pipelines, and GPU acceleration. Each example is designed to be read independently and includes a problem formulation, a parallel implementation, and a discussion of the key Taskflow features at work.
These examples demonstrate how to express parallelism as a static task dependency graph using tf::Taskflow, including conditional and non-deterministic control flow.
| Example | Brief |
|---|---|
| Wavefront Parallelism | Diagonal sweep parallelism over a 2D grid where each cell depends on its left and top neighbours |
| Graph Traversal | Parallel DAG traversal where task dependencies mirror the input graph structure |
| Nondeterministic Control Flow | Stochastic branching using conditional tasks to express non-deterministic execution paths |
| Blocked Cholesky Factorization | Task-parallel blocked Cholesky decomposition based on a tile dependency graph |
| Critical Path Scheduling | PERT chart executed as a static task graph to identify the critical path |
| Incremental Build Graph | Make-style incremental build system using condition tasks |
| Speculative Execution | Bloom filter simualtion using condition tasks |
Links to each example subpage are provided below:
These examples focus on Taskflow's dynamic task creation capabilities, including async tasks, dependent-async task graphs, cooperative execution, and recursive runtime tasking.
| Example | Brief |
|---|---|
| Fibonacci Number | Recursive task parallelism using tf::Runtime and cooperative synchronization via tf::TaskGroup |
| Async Producer-Consumer Pipeline | Overlapping producer, validator, and consumer stages using dependent-async tasks |
| Divide and Conquer | Divide-and-conquer parallelism with tf::TaskGroup, demonstrated on parallel merge sort |
| Dynamic Dependency Graph | Runtime-driven task graph whose topology and dependencies are determined by program data |
| Traveling Salesman Problem | Parallel branch-and-bound solver for the traveling salesman problem |
| Graph Coloring Problem | Parallel branch-and-bound solver for the graph coloring problem |
Links to each example subpage are provided below:
These examples apply Taskflow's parallel algorithms and pipeline scheduling to classic computational and data-processing problems.
| Example | Brief |
|---|---|
| Parallel Breadth-First Search | Parallel BFS using stateful frontier iteration with tf::IndexRange and atomic distance claims |
| Matrix Multiplication | Parallel dense matrix multiplication partitioned across CPU workers |
| K-Means Clustering | Parallel k-means clustering with iterative assignment and centroid update steps |
| 3D Stencil Computation | Parallel 3D Jacobi stencil over a volumetric grid using tf::IndexRange |
| Sparse Matrix-Vector Multiplication | Parallel SpMV in CSR format demonstrating partitioner selection for irregular workloads |
| 2D Image Convolution | Parallel 2D image convolution using tf::IndexRange |
| Text Processing Pipeline | Character frequency analysis expressed as a three-stage parallel pipeline |
| Graph Processing Pipeline | Wavefront pipeline scheduling over a DAG of dependent processing stages |
| Taskflow Processing Pipeline | Nested taskflow graphs embedded inside pipeline stages for hierarchical parallelism |
Links to each example subpage are provided below:
These examples demonstrate how to offload computation to a CUDA GPU using tf::cudaGraph, coordinated with CPU tasks in a single taskflow.
| Example | Brief |
|---|---|
| Matrix Multiplication (CUDA) | GPU-accelerated dense matrix multiplication using tf::cudaGraph coordinated with CPU tasks |
| K-Means Clustering (CUDA) | GPU-accelerated k-means clustering with CUDA kernels for assignment and centroid update |
Links to each example subpage are provided below:
1.13.1
