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Intel software, Wolfram Mathematica, Origin, Statgraphics, EViews
Intel software, Wolfram Mathematica, Origin, Statgraphics, EViews
Info e Commerciali Intel software, Wolfram Mathematica, Origin, Statgraphics, EViews
Intel® Threading Building Blocks 2020 (Intel TBB)
Lingua: Ing S.O.: Win, Linux, MacOS
Produttore: Intel® Software
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Parallel Programming at Your Fingertips

Intel® Threading Building Blocks (Intel® TBB) makes parallel performance and scalability accessible to software developers who are writing loop- and task-based applications. Build robust applications that abstract platform details and threading mechanisms while achieving performance that scales with increasing core count.

 

Overview

Intel® Threading Building Blocks (Intel® TBB) is a widely used C++ library for shared memory parallel programming and heterogeneous computing (intra-node distributed memory programming). The library provides a wide range of features for parallel programming that include:

  • Generic parallel algorithms
  • Concurrent containers
  • A scalable memory allocator
  • Work-stealing task scheduler
  • Low-level synchronization primitives

Use this library-only solution for task-based parallelism. It does not require any special compiler support and has ports to multiple architectures that include Intel® architectures and Arm*.

 

Get the Product

Threading Building Blocks (TBB) is available as a part of the following tool suites.

Intel® Parallel Studio XE

Intel® System Studio

 

What’s New

  • Extended task_arena interface to simplify development of NUMA-aware applications that specifically enable composable, scalable performance within.
  • Continued support for resumable tasks that allow the user to suspend task execution at a specific point and resume it later, which reduces code complexity when integrating I/O threads in compute-intensive applications.
  • Implemented the preview feature.

Release Notes

Threading Building Blocks

 

Features

Parallel Algorithms & Data Structures

  • Generic Parallel Algorithms: An efficient, scalable way to exploit the power of multicore without having to start from scratch.
  • Flow Graph: A set of classes to express parallelism as a graph of compute dependencies or data flows.
  • Concurrent Containers: Concurrent access and a scalable alternative to containers that are externally locked for thread safety.

Memory Allocation & Task Scheduling

  • Task Scheduler: A sophisticated work-scheduling engine that empowers parallel algorithms and the Flow Graph.
  • Memory Allocation: A scalable memory manager and false-sharing free allocators.

Threads & Synchronization

  • Synchronization Primitives: Atomic operations, a variety of mutexes with different properties, and condition variables
  • Timers and Exceptions: Thread-safe timers and exception classes
  • Threads: Operating system API wrappers
  • Thread Local Storage: Efficient implementation for an unlimited number of thread-local variables

Conditional Numerical Reproducibility

Ensure deterministic associativity for floating-point arithmetic results with the new template function: parallel_deterministic_reduce.

Support for C++11 Lambda Expressions

Intel TBB can be used with C++11 compilers and supports lambda expressions. For developers using parallel algorithms, lambda expressions reduce the time and code needed by removing the requirement for separate objects or classes.

 

Benefits

  • Specify logical parallelism instead of threads. Its runtime library automatically maps logical parallelism onto threads in a way that makes efficient use of processor resources, making it less tedious and more efficient.
  • Target threading for performance. The software is also compatible with other threading packages. This gives you the flexibility to leave your legacy code as-is, and use TBB for new implementations.
  • Emphasize data-parallel programming, enabling multiple threads to work on different parts of a collection. This programming scales well to larger numbers of processors by dividing the collection into smaller pieces. Program performance increases as you add processors.
  • Generic programming enables you to write the best possible algorithms with the fewest constraints. For example: Interfaces for the C++ Standard Template Library (STL) are specified by requirements on types.
  • Support heterogeneous computing through the Flow Graph Designer.

 

Support

Paid licenses receive Priority Support where you can connect privately with Intel engineers for technical questions.

Forum

Priority Support

 

Target Workloads

Multithreading is for applications with problems that are massively parallel or can be divided into parallel tasks.

  • Numeric weather prediction
  • Oceanography
  • Astrophysics
  • Social economics
  • Finite element analysis
  • AI and automation
  • Genetic engineering
  • Seismic exploration
  • Weapon research and defense
  • Remote sensing applications
  • Medical applications
  • Energy resource exploration

 

Specs at a Glance

TBB-imm-table.PNG

 

Acquista: Intel® TBB

 
Prova Demo: Intel® TBB