Release Notes » Release 3.0.0 (2021/01/01)

Taskflow 3.0.0 is the 1st release in the 3.x line! This release includes several new changes such as CPU-GPU tasking, algorithm collection, enhanced web-based profiler, documentation, and unit tests.

Download

Taskflow 3.0.0 can be downloaded from here.

System Requirements

To use Taskflow v3.0.0, you need a compiler that supports C++17:

GNU C++ Compiler at least v7.0 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

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

Working Items

enhancing the taskflow profiler (TFProf)
adding methods for updating tf::cudaFlow (with unit tests)
adding support for cuBLAS
adding support for cuDNN
adding support for SYCL (ComputeCpp and DPC++)

New Features

Taskflow Core

replaced all non-standard libraries with C++17 STL (e.g., std::optional, std::variant)
added tf::WorkerView for users to observe the running works of tasks
added asynchronous tasking (see Asynchronous Tasking)
modified tf::ObserverInterface::on_entry and tf::ObserverInterface::on_exit to take tf::WorkerView
added a custom graph interface to support dynamic polymorphism for tf::cudaGraph
supported separate compilations between Taskflow and CUDA (see Compile Taskflow with CUDA)
added tf::Semaphore and tf::CriticalSection to limit the maximum concurrency
added tf::Future to support cancellation of submitted tasks (see Request Cancellation)

cudaFlow

added tf::cudaFlowCapturer for building a cudaFlow through stream capture
added tf::cudaFlowCapturerBase for creating custom capturers
added tf::cudaFlow::capture for capturing a cudaFlow within a parent cudaFlow
added tf::Taskflow::emplace_on to place a cudaFlow on a GPU
added tf::cudaFlow::dump and tf::cudaFlowCapturer::dump to visualize cudaFlow
added tf::cudaFlow::offload and update methods to run and update a cudaFlow explicitly
supported standalone cudaFlow
supported standalone cudaFlowCapturer
added tf::cublasFlowCapturer to support cuBLAS (see LinearAlgebracublasFlowCapturer)

Utilities

added utility functions to grab the cuda device properties (see cuda_device.hpp)
added utility functions to control cuda memory (see cuda_memory.hpp)
added utility functions for common mathematics operations
added serializer and deserializer libraries to support tfprof
added per-thread pool for CUDA streams to improve performance

Taskflow Profiler (TFProf)

added visualization for asynchronous tasks
added server-based profiler to support large profiling data (see Profile Taskflow Programs)

New Algorithms

CPU Algorithms

added parallel sort (see Parallel Sort)

GPU Algorithms

added single task
added parallel iterations
added parallel transforms
added parallel reduction

Bug Fixes

fixed the bug in stream capturing (need to use ThreadLocal mode)
fixed the bug in reporting wrong worker ids when compiling a shared library due to the use of thread_local (now with C++17 inline variable)

Breaking Changes

changed the returned values of asynchronous tasks to be std::optional in order to support cancellation (see Asynchronous Tasking and Request Cancellation)

Deprecated and Removed Items

removed tf::cudaFlow::device; users may call tf::Taskflow::emplace_on to associate a cudaflow with a GPU device
removed tf::cudaFlow::join, use tf::cudaFlow::offload instead
removed the legacy tf::Framework
removed external mutable use of tf::TaskView

Documentation

added Compile Taskflow with CUDA
added Benchmark Taskflow
added Limit the Maximum Concurrency
added Asynchronous Tasking
added GPU Tasking
added Request Cancellation
added Profile Taskflow Programs
added Governance
added Contributing
- Guidelines
- Contributors
revised Conditional Tasking
revised documentation pages for files

Miscellaneous Items

We have presented Taskflow in the following C++ venues with recorded videos:

We have published Taskflow in the following conferences and journals:

Tsung-Wei Huang, "A General-purpose Parallel and Heterogeneous Task Programming System for VLSI CAD," IEEE/ACM International Conference on Computer-aided Design (ICCAD), CA, 2020
Chun-Xun Lin, Tsung-Wei Huang, and Martin Wong, "An Efficient Work-Stealing Scheduler for Task Dependency Graph," IEEE International Conference on Parallel and Distributed Systems (ICPADS), Hong Kong, 2020
Tsung-Wei Huang, Dian-Lun Lin, Yibo Lin, and Chun-Xun Lin, "Cpp-Taskflow: A General-purpose Parallel Task Programming System at Scale," IEEE Transactions on Computer-aided Design of Integrated Circuits and Systems (TCAD), to appear, 2020