Optimize Intel® oneAPI Threading Building Blocks for NUMA Architectures
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Overview
Threading Building Blocks (TBB) is a high-level C++ template library for parallel programming that was developed as a composable, scalable solution for multicore platforms. And in the realm of high-performance computing (HPC), current multisocket non-uniform memory access (NUMA) systems are used with OpenMP*.
But things have changed.
Increasingly many independent software components require parallelism within a single application, especially in AI and video processing and rendering domains. In such environments, performance may degrade without allowing for composability with other components.
The result? Many developers have pulled TBB into NUMA environments…a complex task for even the most seasoned programmers.
This is why Intel is working to simplify the approach.
Join senior software development engineer Alexei Katranov to learn about Intel’s current work and success stories, and to engage in a lively discussion covering:
- A brief overview of NUMA architectures, TBB, and Intel® oneAPI Threading Building Blocks (oneTBB)—a version of this award-winning library that's optimized with oneAPI
- How to use oneTBB features to tune NUMA systems
- Samples from the free ebook Pro TBB: C++ Parallel Programming with Threading Building Blocks
- A sneak peek at upcoming changes to TBB that will make tuning performance on NUMA systems even easier
- A demonstration on combining TBB features to get great performance on a multisocket NUMA server
Get the Software
- Download oneTBB as part of the Intel® oneAPI Base Toolkit.
- Download oneTBB—one of five free Intel® Performance Libraries.
Other Resources
- Visit Intel oneAPI to learn about this initiative, including downloading the essential Intel oneAPI Base Toolkit, which includes oneTBB.
- Try your code in the Intel® Developer Cloud. Sign up to develop, test, and run your solution in this free development sandbox with access to the latest Intel hardware and oneAPI software. No downloads. No configuration steps. No installations.
Alexei Katranov
Software development engineer, Intel Corporation
Develop high-performance, data-centric applications for CPUs, GPUs, and FPGAs with this core set of tools, libraries, and frameworks including LLVM*-based compilers.
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