Nolan’s Notes: Looking Deep Into the Future With X-ray
Knocking Down the Bone Pile: Basics of Component Lead Tinning
Standard of Excellence: Anticipating Customer Needs Early and Often
Intel oneDNN AI Optimizations Enabled as Default in TensorFlow
May 26, 2022 | IntelEstimated reading time: 2 minutes
In the latest release of TensorFlow 2.9, the performance improvements delivered by the Intel® oneAPI Deep Neural Network Library (oneDNN) are turned on by default. This applies to all Linux x86 packages and for CPUs with neural-network-focused hardware features (like AVX512_VNNI, AVX512_BF16, and AMX vector and matrix extensions that maximize AI performance through efficient compute resource usage, improved cache utilization and efficient numeric formatting) found on 2nd Gen Intel Xeon Scalable processors and newer CPUs. These optimizations enabled by oneDNN accelerate key performance-intensive operations such as convolution, matrix multiplication and batch normalization, with up to 3 times performance improvements compared to versions without oneDNN acceleration.
“Thanks to the years of close engineering collaboration between Intel and Google, optimizations in the oneDNN library are now default for x86 CPU packages in TensorFlow. This brings significant performance acceleration to the work of millions of TensorFlow developers without the need for them to change any of their code. This is a critical step to deliver faster AI inference and training and will help drive AI Everywhere,” said Wei Li, Intel vice president and general manager of AI and Analytics.
oneDNN performance improvements becoming available by default in the official TensorFlow 2.9 release will enable millions of developers who already use TensorFlow to seamlessly benefit from Intel software acceleration, leading to productivity gains, faster time to train and efficient utilization of compute. Additional TensorFlow-based applications, including TensorFlow Extended, TensorFlow Hub and TensorFlow Serving also have the oneDNN optimizations. TensorFlow has included experimental support for oneDNN since TensorFlow 2.5.
oneDNN is an open source cross-platform performance library of basic deep learning building blocks intended for developers of deep learning applications and frameworks. The applications and frameworks that are enabled by it can then be used by deep learning practitioners. oneDNN is part of?oneAPI, an open, standards-based, unified programming model for use across CPUs as well as GPUs and other AI accelerators.
While there is an emphasis placed on AI accelerators like GPUs for machine learning and, in particular, deep learning, CPUs continue to play a large role across all stages of the AI workflow. Intel’s extensive software-enabling work makes AI frameworks, such as the TensorFlow platform, and a wide range of AI applications run faster on Intel hardware that is ubiquitous across most personal devices, workstations and data centers. Intel’s rich portfolio of optimized libraries, frameworks and tools serves end-to-end AI development and deployment needs while being built on the foundation of oneAPI.
The oneDNN-driven accelerations to TensorFlow deliver remarkable performance gains that benefit applications spanning natural language processing, image and object recognition, autonomous vehicles, fraud detection, medical diagnosis and treatment and others.
Deep learning and machine learning applications have exploded in number due to increases in processing power, data availability and advanced algorithms. TensorFlow has been one of the world’s most popular platforms for AI application development with over 100 million downloads. Intel-optimized TensorFlow is available both as a standalone component and through the Intel oneAPI AI Analytics Toolkit, and is already being used across a broad range of industry applications including the Google Health project, animation filmmaking at Laika Studios, language translation at Lilt, natural language processing at IBM Watson and many others.
Share on:
Suggested Items
New Splitting Method: Fraunhofer IIS Brings Satellites Into The 5G Era
04/04/2025 | Fraunhofer IAFGlobal mobile communications that reliably reach every remote region, leaving no gaps on the map? Satellites play a key role in achieving this goal. In the future, however, not all satellites will be powerful enough to act as complete base stations.
Ansys Semiconductor Solutions Certified by TSMC for Reliable, Accurate Analysis of Evolving Chip Designs
04/03/2025 | PRNewswireAnsys announced that PathFinder-SC is certified as a new ESD analysis solution for customers designing with TSMC's N2 silicon process technology. PathFinder-SC delivers a novel verification solution that provides superior capacity and performance, easily accommodating large designs in the cloud.
Molex Releases New Report on Strategies for Advancing Rugged, Reliable Connectivity in Modern Aerospace and Defense Applications
04/01/2025 | MolexMolex, a global electronics leader and connectivity innovator, has released a new report from AirBorn, a Molex company, which explores the unrelenting demands for constant, continuous connectivity to support the rigors of modern aerospace, defense and space-industry applications.
The Rise of Refurbished Laptops and Computers: A Sustainable and Smart Alternative
03/28/2025 | Persistence Market Research Pvt. Ltd.In the fast-paced world of technology, staying ahead with the latest gadgets can be costly. However, the growing market for refurbished laptops and computers is proving to be a game-changer.
Meyer Burger, Memodo Sign Supply Agreement for Italy
03/28/2025 | Meyer BurgerMeyer Burger Technology AG and photovoltaic distributor Memodo have signed a supply agreement. The high-performance modules “Made in Germany” were manufactured at the Freiberg plant in Germany and are intended for the Italian market.