Intel’s PyTorch 2.5 Receives Significant Contributions, Uplifting AI Development to New Heights

Intel has recently released PyTorch 2.5, which offers expanded support for Intel GPUs, providing developers working in artificial intelligence (AI) with enhanced machine learning workflows. The supported GPUs include Intel Arc discrete graphics, Intel Core Ultra processors with built-in Intel Arc graphics, and Intel Data Center GPU Max Series.

These new features aim to promote accelerated machine learning workflows within the PyTorch ecosystem, ensuring a consistent developer experience and support. Developers and researchers who want to fine-tune, inference, and experiment with PyTorch models on Intel Core Ultra AI PCs can now directly install PyTorch with preview and nightly binary releases for Windows, Linux, and Windows Subsystem for Linux 2.

The key features of PyTorch 2.5 include an expanded hardware backend support matrix that includes both Intel Data Center and Client GPUs. This allows developers to leverage the power of Intel GPUs for their AI workloads. Additionally, the implementation of SYCL kernels enhances the coverage and execution of Aten operators on Intel GPUs, resulting in improved performance in PyTorch eager mode. The Intel GPU backend of torch.compile has also been enhanced to boost inference and training performance for a wide range of deep learning workloads.

PyTorch 2.5 also brings improvements and new features specifically for the latest Intel data center CPUs. The FP16 datatype is now enabled and optimized through Intel Advanced Matrix Extensions, enhancing inference capabilities on platforms like Intel Xeon processors. The TorchInductor C++ backend is also available on Windows, providing a better user experience for AI developers in Windows environments.

It’s important to note that the performance results mentioned are based on specific testing configurations and may not reflect all publicly available updates. Intel does not control or audit third-party data, so it’s advisable to consult other sources for accuracy evaluation.

Background Information

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About Intel: Intel Corporation, a global technology leader, is renowned for its semiconductor innovations that power computing and communication devices worldwide. As a pioneer in microprocessor technology, Intel has left an indelible mark on the evolution of computing with its processors that drive everything from PCs to data centers and beyond. With a history of groundbreaking advancements, Intel's relentless pursuit of innovation continues to shape the digital landscape, offering solutions that empower businesses and individuals to achieve new levels of productivity and connectivity.

  

Technology Explained

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GPU: GPU stands for Graphics Processing Unit and is a specialized type of processor designed to handle graphics-intensive tasks. It is used in the computer industry to render images, videos, and 3D graphics. GPUs are used in gaming consoles, PCs, and mobile devices to provide a smooth and immersive gaming experience. They are also used in the medical field to create 3D models of organs and tissues, and in the automotive industry to create virtual prototypes of cars. GPUs are also used in the field of artificial intelligence to process large amounts of data and create complex models. GPUs are becoming increasingly important in the computer industry as they are able to process large amounts of data quickly and efficiently.

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Xeon: The Intel Xeon processor is a powerful and reliable processor used in many computer systems. It is a multi-core processor that is designed to handle multiple tasks simultaneously. It is used in servers, workstations, and high-end desktop computers. It is also used in many embedded systems, such as routers and switches. The Xeon processor is known for its high performance and scalability, making it a popular choice for many computer applications. It is also used in many cloud computing applications, as it is capable of handling large amounts of data and providing high levels of performance. The Xeon processor is also used in many scientific and engineering applications, as it is capable of handling complex calculations and simulations.