AMD introduces ROCm and PyTorch Compatible Driver for Radeon RX 7900 XTX, Empowering Graphics Enthusiasts

Gaming RX 7900 XTX Navi 31 support for PyTorch and ROCm on Linux

AMD has recently rolled out a new driver for Ubuntu, bringing support for consumer Radeon GPUs. This driver update is particularly significant for the AI community as it introduces PyTorch compatibility for AMD’s consumer Radeon GPUs and Radeon PRO, through the ROCm 5.7.1 platform.

PyTorch, an open-source deep learning library developed by Facebook AI Research, has gained popularity among various companies and enjoys extensive support from CPU and GPU manufacturers. Initially, AMD’s response to integrating PyTorch support for their consumer Radeon GPUs and Radeon PRO was slow. However, with the release of ROCm 5.7.1, there is a notable shift in their approach.

The latest version of Radeon Software for Linux, specifically Ubuntu 22.04.03 HEW, brings PyTorch 2.0.1 support via ROCm for two RDNA3-based GPUs: the PRO W7900 and RX 7900 XT. This marks the first official instance of AMD enabling ROCm support for the RX 7900 XTX.

Dan Wood, Corp. Vice President of Radeon Product Management at AMD, expressed excitement about offering the AI community new support for machine learning development using PyTorch on the AMD Radeon RX 7900 XTX and Radeon PRO W7900 GPUs, along with the ROCm open software platform. He also mentioned that this implementation is based on the RDNA 3 architecture, and AMD is eager to collaborate with the community.

While it hasn’t been explicitly confirmed whether lower SKUs will receive support as well, AMD is currently focusing on the high memory capacities of 24GB (7900 XTX) and 48GB (W7900). The Radeon 7900 series, powered by the Navi 31 GPU, boasts 192 AI Accelerators, which AMD claims can deliver up to 2x higher performance compared to the previous generation (Radeon PRO W6800 with Navi 21).

AMD’s commitment to extending support for machine learning applications in consumer-grade products is commendable. This move makes affordable workstation builds a reality, as the line between gaming and professional GPUs continues to blur. The emphasis on AI-accelerated applications is shifting towards open-source software optimized for cost-effective processors. While AMD Radeon Pro and nVidia RTX workstations may offer more memory, their higher cost can be a significant concern for individuals starting their AI learning journey.

In conclusion, AMD’s latest driver update for Ubuntu brings PyTorch support to their consumer Radeon GPUs and Radeon PRO, enabling the AI community to leverage the power of machine learning development. With the introduction of ROCm 5.7.1 and the RDNA 3 architecture-based implementation, AMD is making strides in providing affordable solutions for AI-accelerated applications.

Source: AMD Blog, AMD driver

Background Information

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About AMD:

AMD, a large player in the semiconductor industry is known for its powerful processors and graphic solutions, AMD has consistently pushed the boundaries of performance, efficiency, and user experience. With a customer-centric approach, the company has cultivated a reputation for delivering high-performance solutions that cater to the needs of gamers, professionals, and general users. AMD's Ryzen series of processors have redefined the landscape of desktop and laptop computing, offering impressive multi-core performance and competitive pricing that has challenged the dominance of its competitors. Complementing its processor expertise, AMD's Radeon graphics cards have also earned accolades for their efficiency and exceptional graphical capabilities, making them a favored choice among gamers and content creators. The company's commitment to innovation and technology continues to shape the client computing landscape, providing users with powerful tools to fuel their digital endeavors.

  

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About nVidia:

NVIDIA has firmly established itself as a leader in the realm of client computing, continuously pushing the boundaries of innovation in graphics and AI technologies. With a deep commitment to enhancing user experiences, NVIDIA's client computing business focuses on delivering solutions that power everything from gaming and creative workloads to enterprise applications. for its GeForce graphics cards, the company has redefined high-performance gaming, setting industry standards for realistic visuals, fluid frame rates, and immersive experiences. Complementing its gaming expertise, NVIDIA's Quadro and NVIDIA RTX graphics cards cater to professionals in design, content creation, and scientific fields, enabling real-time ray tracing and AI-driven workflows that elevate productivity and creativity to unprecedented heights. By seamlessly integrating graphics, AI, and software, NVIDIA continues to shape the landscape of client computing, fostering innovation and immersive interactions in a rapidly evolving digital world.

  

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Technology Explained

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CPU: The Central Processing Unit (CPU) is the brain of a computer, responsible for executing instructions and performing calculations. It is the most important component of a computer system, as it is responsible for controlling all other components. CPUs are used in a wide range of applications, from desktop computers to mobile devices, gaming consoles, and even supercomputers. CPUs are used to process data, execute instructions, and control the flow of information within a computer system. They are also used to control the input and output of data, as well as to store and retrieve data from memory. CPUs are essential for the functioning of any computer system, and their applications in the computer industry are vast.

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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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Navi 31: Navi 31 is a new technology developed by AMD that is designed to improve the performance of computer graphics. It is based on the RDNA 2 architecture and is the first GPU to feature the new Infinity Cache technology. This technology allows for faster data access and improved memory bandwidth, resulting in improved performance for gaming and other graphics-intensive applications. Navi 31 also features improved ray tracing capabilities, allowing for more realistic lighting and shadows in games and other applications. Additionally, Navi 31 is designed to be more power efficient, allowing for longer battery life in laptops and other mobile devices. Overall, Navi 31 is a powerful new technology that is sure to revolutionize the computer industry.

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Radeon: AMD Radeon, a product line by Advanced Micro Devices (AMD), consists of graphics processing units (GPUs) recognized for their strong performance in gaming, content creation, and professional applications. Powered by innovative technologies like the RDNA architecture, Radeon GPUs deliver efficient and powerful graphics processing. The brand also supports features like FreeSync, enhancing visual fluidity and reducing screen tearing during gaming. Moreover, AMD Radeon GPUs embrace real-time ray tracing for heightened realism in lighting and reflections. With a balance between price and performance, Radeon competes with NVIDIA's GeForce graphics cards and remains a popular choice for a wide range of users.

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RDNA: RDNA (Radeon DNA) is a graphics architecture developed by Advanced Micro Devices (AMD) for its Radeon series of graphics cards. It's designed to deliver improved performance, power efficiency, and advanced features for gaming and graphics-intensive applications. RDNA introduces a new compute unit design that enhances the efficiency of processing tasks, resulting in better performance per watt compared to its predecessor, GCN (Graphics Core Next). RDNA also introduces hardware-based ray tracing capabilities, allowing for more realistic lighting, shadows, and reflections in supported games. With its scalable design, RDNA architecture addresses the demands of modern gaming while aiming to provide a more immersive and visually impressive experience.

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