Release 3.7.0 (2024/05/07)

Table of Contents

• Download
• System Requirements
• Release Summary
• New Features
  • Taskflow Core
  • Utilities
• Bug Fixes
• Breaking Changes
• Documentation
• Miscellaneous Items

Taskflow 3.7.0 is the 8th release in the 3.x line! This release includes several new changes, such as exception support, improved scheduling algorithms, documentation, examples, and unit tests.

Download

Taskflow 3.7.0 can be downloaded from here.

System Requirements

To use Taskflow v3.7.0, you need a compiler that supports C++17:

• GNU C++ Compiler at least v8.4 with -std=c++17
• Clang C++ Compiler at least v6.0 with -std=c++17
• Microsoft Visual Studio at least v19.27 with /std:c++17
• AppleClang Xcode Version at least v12.0 with -std=c++17
• Nvidia CUDA Toolkit and Compiler (nvcc) at least v11.1 with -std=c++17
• Intel C++ Compiler at least v19.0.1 with -std=c++17
• Intel DPC++ Clang Compiler at least v13.0.0 with -std=c++17

Taskflow works on Linux, Windows, and Mac OS X.

Release Summary

This release introduces a new exception interface to help identify C++ errors in taskflow programs.

New Features

Taskflow Core

• Improved scheduling performance of dependent asynchronous tasks
• Improved scheduling performance of module task by removing busy looping
• Improved tf::Executor::wait_for_all using C++20 atomic wait
• Improved tf::Notifier using C++20 atomic wait
• Improved worker-thread ID mapping performance using C++20 atomic wait
• Added -Wshadow to the compilation check
• Added tf::AsyncTask::is_done to query the completion status of an async task
• Added tf::Taskflow::remove_dependency to remove dependencies from the graph
• Added support for exception in tf::Taskflow and tf::Executor

tf::Executor executor;
tf::Taskflow taskflow;
taskflow.emplace([](){ throw std::runtime_error("exception"); });
try {
  executor.run(taskflow).get();
}
catch(const std::runtime_error& e) {
  std::cerr << e.what() << std::endl;
}

• Modified the CI to exclude exception test under sanitizers
• Modified the tf::PartitionerBase to allow defining custom closure wrappers

std::atomic<int> count = 0;
tf::Taskflow taskflow;
taskflow.for_each_index(0, 100, 1, 
  [](){                 
    printf("%d\n", i); 
  },
  tf::StaticPartitioner(0, [](auto&& closure){
    // do something before invoking the partitioned task
    // ...
    
    // invoke the partitioned task
    closure();
 
    // do something else after invoking the partitioned task
    // ...
  }
);
executor.run(taskflow).wait();

Utilities

Bug Fixes

• Fixed compilation error of CUDA examples caused by not including for_each.hpp
• Fixed the runtime error of tf::Taskflow::for_each_index when the range invalid

Breaking Changes

• Renamed tf::Runtime::join to tf::Runtime::corun_all
• Removed tf::WorkerInterface due to the support of exception

Documentation

• Revised Asynchronous Tasking with Dependencies
  • Added Query the Completion Status of Dependent Async Tasks
• Revised Exception Handling
• Revised Executor
  • Removed the section of tf::WorkerInterface
• Revised Partitioning Algorithm

Miscellaneous Items

We have published Taskflow in the following venues:

• Cheng-Hsiang Chiu, Zhicheng Xiong, Zizheng Guo, Tsung-Wei Huang, and Yibo Lin, "An Efficient Task-parallel Pipeline Programming Framework," ACM International Conference on High-performance Computing in Asia-Pacific Region (HPC Asia), Nagoya, Japan, 2024
• Cheng-Hsiang Chiu, Dian-Lun Lin, and Tsung-Wei Huang,, "Programming Dynamic Task Parallelism for Heterogeneous EDA Algorithms," IEEE/ACM International Conference on Computer-aided Design (ICCAD), San Francisco, CA, 2023

Please do not hesitate to contact Dr. Tsung-Wei Huang if you intend to collaborate with us on using Taskflow in your scientific computing projects.