What are the main features of oneapi-src/onetbb?

The main features of oneapi-src/onetbb are: C++ Parallel Programming, Data Parallelism Scaling, Dynamic Load Balancing, Work-Stealing Schedulers, Logical Parallelism Mapping, Multi-Core Scheduling, Multi-Core Scaling Libraries, C++ Parallelism Libraries.

What are some open-source alternatives to oneapi-src/onetbb?

Open-source alternatives to oneapi-src/onetbb include: uxlfoundation/onetbb — oneAPI Threading Building Blocks (oneTBB). thrust/thrust — Thrust is a heterogeneous computing library and C++ template library that provides a collection of high-level… ocaml/ocaml — OCaml is a strongly typed functional language featuring a sophisticated type system and a focus on safety and… taskflow/taskflow — Taskflow is a C++ task-parallel framework designed to build high-performance parallel workflows and complex dependency… higherorderco/hvm2 — HVM2 is a high-performance execution environment for pure functional programs, implemented as a systems-level runtime… nvidia/thrust — Thrust is a C++ parallel algorithms library that provides a suite of standard-library-inspired interfaces for…

OneTBB - parallelize C++ applications on mult…

oneTBB is a C++ parallelism library and framework designed to add multi-core parallelism to applications. It provides a task-based parallelism model that maps logical computational tasks to available hardware cores to eliminate the need for manual thread management.

The library functions as a multi-core scaling tool, utilizing generic templates to scale data-parallel operations across processors for portable performance. It employs a task-based framework to ensure computational workloads are distributed across hardware resources.

The project covers shared memory parallelism, multi-core task scheduling, and data parallelism scaling. It utilizes a work-stealing task scheduler, recursive range splitting, and dynamic load balancing to manage the distribution of work across cores at runtime.

Features

C++ Parallel Programming - Provides a comprehensive framework for implementing multi-core execution in C++ applications without manual thread management.
Data Parallelism Scaling - Enables running operations across large datasets using templates to ensure portable performance across different multi-core processors.
Dynamic Load Balancing - Implements runtime adjustments to workload distribution across cores to prevent individual processor bottlenecks.
Work-Stealing Schedulers - Ships a work-stealing scheduler that dynamically balances computational tasks across hardware threads.
Logical Parallelism Mapping - Automatically assigns computational tasks to available hardware cores to eliminate the need for manual thread management.
Multi-Core Scheduling - Distributes computational workloads across available processor cores to optimize hardware utilization and execution speed.
Multi-Core Scaling Libraries - Offers a set of generic templates and tools for scaling data-parallel operations across processors for portable performance.
C++ Parallelism Libraries - Provides a library for adding multi-core parallelism to applications through task scheduling and data-parallel templates.
Parallelism Templates - Utilizes generic C++ templates to decouple algorithmic logic from underlying hardware resource management for portable performance.
Parallel Computing Implementation - Provides strategies for scaling computational throughput across multiple CPU cores in C++ applications.
Data-Parallel Scaling - Executes data-parallel operations across multi-core processors using generic templates for portable and scalable performance.
Parallel Task Execution - Implements a model for executing multiple asynchronous computations simultaneously and aggregating their results.
Task-Based Concurrency Frameworks - Implements a framework that maps logical computational tasks to available hardware cores to avoid manual thread management.
Recursive Range Splitting - Divides large datasets into smaller sub-ranges recursively until they reach a grain size suitable for parallel execution.
Shared Memory Parallelism - Facilitates the development of applications that execute multiple tasks simultaneously within a single shared memory space.
Thread Pool Abstractions - Provides an abstraction layer that maps logical parallel tasks to a pool of worker threads, hiding physical thread management.
Development Environments - Template library for implementing parallel programming on multi-core processors.

uxlfoundation/oneTBB

6,678View on GitHub

oneAPI Threading Building Blocks (oneTBB)

thrust/thrust

5,003View on GitHub

Thrust is a heterogeneous computing library and C++ template library that provides a collection of high-level templates for executing data-parallel operations. It functions as a parallel algorithms library designed to work across different hardware backends, including multicore CPUs and NVIDIA GPU hardware. The framework utilizes a header-only implementation and a generic-programming policy interface to abstract the differences between CPU and GPU memory and execution models. It employs an iterator-based data abstraction to provide a uniform interface for accessing elements across host RAM an

ocaml/ocaml

6,514View on GitHub

OCaml is a strongly typed functional language featuring a sophisticated type system and a focus on safety and expressiveness. It provides a comprehensive compiling toolchain that transforms source code into either portable bytecode or high-performance native binaries. The project is distinguished by a shared memory parallel runtime that executes computations across multiple processor cores using domains, and an algebraic effect system for managing side effects and control flow through execution context handlers. It also includes a dedicated parser generator to automatically create lexers and

uxlfoundation/oneTBB

6,678View on GitHub

oneAPI Threading Building Blocks (oneTBB)

Taskflow is a C++ task-parallel framework designed to build high-performance parallel workflows and complex dependency graphs. It provides a programming model that organizes computational work into directed acyclic graphs, enabling developers to manage concurrency, resource scheduling, and task dependencies across multi-core CPUs and GPU accelerators. The framework distinguishes itself through its ability to orchestrate heterogeneous systems, allowing for the integration of hardware-accelerated kernels and memory operations into unified execution pipelines. It supports dynamic runtime subflow

oneapi-srconeTBB

OneTBB

Features

Open-source alternatives to OneTBB

uxlfoundation/oneTBB

thrust/thrust

ocaml/ocaml

Frequently asked questions

Star history

Frequently asked questions

Open-source alternatives to OneTBB

uxlfoundation/oneTBB

thrust/thrust

ocaml/ocaml

taskflow/taskflow