Threading Building Blocks

Threading Building Blocks
Developer(s)	Intel

Stable release	2017 / September 6, 2016 (2016-09-06)^[1]^[2]
Written in	C++
Operating system	FreeBSD, Linux, Solaris, OS X, Windows, Android
Type	library or framework
License	dual: commercial / open source (Apache 2.0), plus Freeware^[3]
Website	www.threadingbuildingblocks.org software.intel.com/en-us/intel-tbb

Threading Building Blocks (TBB) is a C++ template library developed by Intel for parallel programming on multi-core processors. Using TBB, a computation is broken down into tasks that can run in parallel. The library manages and schedules threads to execute these tasks.

Overview

A TBB program creates, synchronizes and destroys graphs of dependent tasks according to algorithms, i.e. high-level parallel programming paradigms (a.k.a. Algorithmic Skeletons). Tasks are then executed respecting graph dependencies. This approach groups TBB in a family of solutions for parallel programming aiming to decouple the programming from the particulars of the underlying machine.

TBB implements work stealing to balance a parallel workload across available processing cores in order to increase core utilization and therefore scaling. Initially, the workload is evenly divided among the available processor cores. If one core completes its work while other cores still have a significant amount of work in their queue, TBB reassigns some of the work from one of the busy cores to the idle core. This dynamic capability decouples the programmer from the machine, allowing applications written using the library to scale to utilize the available processing cores with no changes to the source code or the executable program file. In a 2008 assessment of the work stealing implementation in TBB, researchers from Princeton University found that it was suboptimal for large numbers of processors cores, causing up to 47% of computing time spent in scheduling overhead when running certain benchmarks on a 32-core system.^[4]

TBB, like the STL (and the part of the C++ standard library based on it), uses templates extensively. This has the advantage of low-overhead polymorphism, since templates are a compile-time construct which modern C++ compilers can largely optimize away.

Intel TBB is available commercially as a binary distribution with support,^[5] and as open-source software in both source and binary forms.^[6]

TBB does not provide guarantees of determinism or freedom from data races.^[7]

Library contents

TBB is a collection of components for parallel programming:

Basic algorithms: parallel_for, parallel_reduce, parallel_scan
Advanced algorithms: parallel_while, parallel_do, parallel_pipeline, parallel_sort
Containers: concurrent_queue, concurrent_priority_queue, concurrent_vector, concurrent_hash_map
Memory allocation: scalable_malloc, scalable_free, scalable_realloc, scalable_calloc, scalable_allocator, cache_aligned_allocator
Mutual exclusion: mutex, spin_mutex, queuing_mutex, spin_rw_mutex, queuing_rw_mutex, recursive_mutex
Atomic operations: fetch_and_add, fetch_and_increment, fetch_and_decrement, compare_and_swap, fetch_and_store
Timing: portable fine grained global time stamp
Task scheduler: direct access to control the creation and activation of tasks

Systems supported

The TBB commercial release 3.0 supports Windows (XP or newer), OS X (version 10.5.8 or higher) and Linux using Visual C++ (version 8.0 or higher, on Windows only), Intel C++ Compiler (version 11.1 or higher) or the GNU Compiler Collection (gcc).^[8] Additionally, the TBB open source community has contributed patches for Solaris,^[9] PowerPC, Xbox 360, QNX Neutrino, and FreeBSD.

Notes

↑ "What's New? Intel® Threading Building Blocks 2017".
↑ "Intel Threading Building Blocks Release Notes".
↑ "No Cost Options for Intel Parallel Studio XE, Support yourself, Royalty-Free".
↑ Contreras, Gilberto; Martonosi, Margaret (2008). Characterizing and improving the performance of Intel Threading Building Blocks (PDF). IEEE Int'l Symp. on Workload Characterization.
↑ http://www.threadingbuildingblocks.com Intel Threading Building Blocks Commercial Version Homepage
↑ http://www.threadingbuildingblocks.org Threading Building Blocks Open Source Project Homepage
↑ Bocchino Jr., Robert L.; Adve, Vikram S.; Adve, Sarita V.; Snir, Marc (2009). Parallel Programming Must Be Deterministic by Default. USENIX Workshop on Hot Topics in Parallelism.
↑ "Intel Threading Building Blocks - Release Notes Version 3.0". Retrieved 2011-08-08.
↑ "Using Intel's Threaded Building Blocks (TBB) With Sun Studio Express". Retrieved 2008-05-08.

References

Reinders, James (July 2007), Intel Threading Building Blocks: Outfitting C++ for Multi-core Processor Parallelism (Paperback ed.), Sebastopol: O'Reilly Media, ISBN 978-0-596-51480-8
Voss, M. (October 2006), Demystify Scalable Parallelism with Intel Threading Building Blocks' Generic Parallel Algorithms
Voss, M. (December 2006), Enable Safe, Scalable Parallelism with Intel Threading Building Blocks' Concurrent Containers
Hudson, Richard L.; Saha, Bratin; Adl-Tabatabai, Ali-Reza; Hertzberg, Benjamin C. (2006), "McRT-Malloc", Proceedings of the 2006 international symposium on Memory management - ISMM '06, pp. 74–83, doi:10.1145/1133956.1133967, ISBN 1595932216

External links

Intel software

Items in italics are no longer maintained or have planned end-of-life dates.

Development	Parallel Studio C++ Compiler Fortran Compiler Debugger Parallel Advisor Parallel Inspector VTune Array Visualizer Cilk Plus

Components	Integrated Performance Primitives (IPP) Math Kernel Library (MKL) Threading Building Blocks (TBB) Concurrent Collections for C++ (CnC) Parallel Building Blocks (PBB) Intel Array Building Blocks (ArBB) Ct Indeo

Open source	Threading Building Blocks (TBB) Cilk Plus Concurrent Collections for C++ (CnC) Moblin MeeGo Tizen

Software programs	Telekinesys Research¹ Havok¹ Vision¹ Intel Security SiteAdvisor Stonesoft VirusScan Validate Wind River Systems Simics VxWorks

Organizations	Developer Zone AppUp Research

¹Sold

Parallel computing

General	Distributed computing Cloud computing High-performance computing

Levels	Bit Instruction Task Data Memory Loop Pipeline

Multithreading	Temporal Simultaneous Preemptive Cooperative

Theory	PRAM model Analysis of parallel algorithms Amdahl's law Gustafson's law Cost efficiency Karp–Flatt metric Slowdown Speedup

Elements	Process Thread Fiber Instruction window

Coordination	Multiprocessing Memory coherency Cache coherency Cache invalidation Barrier Synchronization Application checkpointing

Programming	Stream Processing Dataflow programming Models Implicit parallelism Explicit parallelism Concurrency Non-blocking algorithm

Hardware	Flynn's taxonomy SISD SIMD MISD MIMD Dataflow architecture Pipelined processor Superscalar processor Vector processor Multiprocessor symmetric asymmetric Memory shared distributed distributed shared UMA NUMA COMA Massively parallel computer Computer cluster Grid computer

APIs	Ateji PX Boost.Thread Charm++ Cilk Coarray Fortran CUDA Dryad C++ AMP Global Arrays MPI OpenMP OpenCL OpenHMPP OpenACC TPL PLINQ PVM POSIX Threads RaftLib UPC TBB

Problems	Embarrassingly parallel Software lockout Scalability Race condition Deadlock Livelock Starvation Deterministic algorithm Parallel slowdown

Category: parallel computing Media related to parallel computing at Wikimedia Commons

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