Release Notes » Release 3.7.0 (2024/05/07) | Taskflow QuickStart

# Release Notes » Release 3.7.0 (2024/05/07)

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. Additionally, this release enhances the scheduling performance through integration of C++20 atomic-wait into scheduler, executor, and notifier.

#### Note

When compiling Taskflow with C++20, applications should see improved performance due to the new atomic-wait/-notification algorithm powered by C++20.

## 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.

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