Intel threading building blocks - outfitting C++ for multi-core processor parallelism

By J. Reinders. 2007

907 citations recorded by the source corpus.

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The deal.II finite element library: Design, features, and insights (2019, methodology): “II are parallelized using task-based programming (currently via the Threading Building Blocks library [27]), with higher level abstractions building on these concepts [21].”
Shenango: Achieving High CPU Efficiency for Latency-sensitive Datacenter Workloads (2019, background): “Examples include Capriccio [73], Lithe [58], Intel’s TBB [64], µThreads [14], Arachne [63], and the Go runtime [6].”
Optimizing data-intensive computations in existing libraries with split annotations (2018, methodology): “Each function parallelizes work using a framework such as Intel TBB [62] and is hand-optimized using SIMD instructions.”
Piccolo: Building Fast, Distributed Programs with Partitioned Tables (2010, background): “For multicore CPUs, Cilk [8] and more recently, Intel’s Thread Building Blocks [41] provide support for low-overhead thread creation and dispatching of tasks at a fine level.”
3D is here: Point Cloud Library (PCL) (2011, methodology): “In addition, PCL provides support for OpenMP (see http://openmp.org) and Intel Threading Building Blocks (TBB) library [ 2 ] for multi-core parallelization.”
Larrabee: a many-core x86 architecture for visual computing (2008, methodology): “A production implementation of such a task programming API can be found in Intel Thread Building Blocks [Reinders 2007].”