Increase Deep Learning Framework Performance on CPUs and GPUs
Develop Faster Deep Learning Frameworks and Applications
The Intel® oneAPI Deep Neural Network Library (oneDNN) provides highly optimized implementations of deep learning building blocks. With this open source, cross-platform library, deep learning application and framework developers can use the same API for CPUs, GPUs, or both—it abstracts out instruction sets and other complexities of performance optimization.
Using this library, you can:
Improve performance of frameworks you already use, such as OpenVINO™ toolkit, AI Tools from Intel, PyTorch*, and TensorFlow*.
Develop faster deep learning applications and frameworks using optimized building blocks.
Deploy applications optimized for Intel CPUs and GPUs without writing any target-specific code.
Download as Part of the Toolkit
oneDNN is included as part of the Intel® oneAPI Base Toolkit, which is a core set of tools and libraries for developing high-performance, data-centric applications across diverse architectures.
Build and optimize oneAPI multiarchitecture applications using the latest Intel-optimized oneAPI and AI tools, and test your workloads across Intel® CPUs and GPUs. No hardware installations, software downloads, or configuration necessary.
Preparing for Aurora: Ensuring the Portability of Deep Learning Software to Explore Fusion Energy
Argonne National Laboratory ported FusionDL, a collection of machine learning models and implementations in multiple frameworks, including TensorFlow and PyTorch optimized by oneDNN, to the Aurora exascale supercomputer.
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