AMD introduces Data Center AI Solutions: Introducing AMD Instinct MI300 Series


December 7, 2023 by our News Team

AMD has launched its latest products in the AI and HPC space, including the AMD Instinct MI300X accelerators and the AMD Instinct MI300A APU, which boast impressive performance capabilities and have already gained support from major OEMs and partnerships.

  • Industry-leading memory bandwidth for generative AI
  • Superior performance for large language model training and inferencing
  • Significant improvements over previous generation models


In a major announcement, AMD has launched its latest products in the AI and HPC space – the AMD Instinct MI300X accelerators and the AMD Instinct MI300A accelerated processing unit (APU). These new products boast impressive performance capabilities and are set to make waves in the industry.

The AMD Instinct MI300X accelerators are designed to deliver industry-leading memory bandwidth for generative AI and offer superior performance for large language model (LLM) training and inferencing. With advanced technologies and leadership hardware, these accelerators are expected to be deployed on a large scale in cloud and enterprise environments. Microsoft is already onboard, having recently announced the Azure ND MI300x v5 Virtual Machine series powered by AMD Instinct MI300X accelerators.

On the other hand, the AMD Instinct MI300A APU combines the power of the latest AMD CDNA 3 architecture and “Zen 4” CPUs to provide breakthrough performance for HPC and AI workloads. The El Capitan supercomputer, housed at Lawrence Livermore National Laboratory, is set to be one of the first exascale-class supercomputers powered by this APU, capable of delivering more than two exaflops of double precision performance.

Several major OEMs have also showcased their support for AMD’s new products. Dell presented the Dell PowerEdge XE9680 server featuring eight AMD Instinct MI300 Series accelerators, while HPE announced the HPE Cray Supercomputing EX255a, the first supercomputing accelerator blade powered by the AMD Instinct MI300A APU. Lenovo is also planning to support the new AMD Instinct MI300 Series accelerators in their designs, with availability expected in the first half of 2024.

The AMD Instinct MI300X accelerators, powered by the new CDNA 3 architecture, offer significant improvements over their predecessors. With nearly 40% more Compute Units, 1.5x more memory capacity, and 1.7x more peak theoretical memory bandwidth, these accelerators are optimized for AI and HPC workloads. They feature an impressive 192 GB of HBM3 memory capacity and 5.3 TB/s peak memory bandwidth, making them ideal for demanding AI workloads.

In terms of performance, the AMD Instinct Platform outperforms the nVidia H100 HGX, offering up to 1.6x throughput increase when running inference on LLMs like BLOOM 176B. It is also capable of running inference for a 70B parameter model, like Llama2, on a single MI300X accelerator, simplifying enterprise-class LLM deployments and providing excellent total cost of ownership.

The AMD Instinct MI300A APUs, the world’s first data center APUs for HPC and AI, leverage 3D packaging and the 4th Gen AMD Infinity Architecture to deliver exceptional performance on critical workloads at the intersection of HPC and AI. With high-performance GPU cores, the latest Zen 4 CPU cores, and 128 GB of next-generation HBM3 memory, these APUs offer approximately 1.9x the performance-per-watt on FP32 HPC and AI workloads compared to previous generation models.

Energy efficiency is a key focus for AMD, and the integration of CPU and GPU cores on a single package in the MI300A APUs provides both efficiency and compute performance for training the latest AI models. AMD aims to achieve a 30x energy efficiency improvement in server processors and accelerators for AI training and HPC from 2020 to 2025, setting a high bar for innovation in this space.

To complement its hardware products, AMD has also announced the latest version of its ROCm software platform – ROCm 6. This open software platform enhances AI acceleration performance by approximately 8x when running on MI300 Series accelerators in Llama 2 text generation compared to previous hardware and software. It also introduces support for several new key features for generative AI, including FlashAttention, HIPGraph, and vLLM. By leveraging widely used open-source AI software models and frameworks, AMD is driving innovation and simplifying the deployment of its AI solutions.

In addition to its software capabilities, AMD is investing in strategic partnerships and acquisitions to further enhance its products. With partnerships like Lamini and MosaicML, and acquisitions of Nod.AI and Mipsology, AMD is expanding its ecosystem and unlocking the true potential of generative AI.

Overall, AMD’s latest announcements in the AI and HPC space demonstrate the company’s commitment to delivering technology and empowering enterprises to adopt and deploy AI-powered solutions. With industry-leading performance, advanced hardware and software technologies, and strategic partnerships, AMD is poised to make a significant impact in the AI and HPC markets.

AMD introduces Data Center AI Solutions: Introducing AMD Instinct MI300 Series

AMD introduces Data Center AI Solutions: Introducing AMD Instinct MI300 Series

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Background Information


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 Dell:

Dell is a globally technology leader providing comprehensive solutions in the field of hardware, software, and services. for its customizable computers and enterprise solutions, Dell offers a diverse range of laptops, desktops, servers, and networking equipment. With a commitment to innovation and customer satisfaction, Dell caters to a wide range of consumer and business needs, making it a important player in the tech industry.

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About Lenovo:

Lenovo, formerly known as "Legend Holdings," is a important global technology company that offers an extensive portfolio of computers, smartphones, servers, and electronic devices. Notably, Lenovo acquired IBM's personal computer division, including the ThinkPad line of laptops, in 2005. With a strong presence in laptops and PCs, Lenovo's products cater to a wide range of consumer and business needs. Committed to innovation and quality, Lenovo delivers reliable and high-performance solutions, making it a significant player in the tech industry.

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About Microsoft:

Microsoft, founded by Bill Gates and Paul Allen in 1975 in Redmond, Washington, USA, is a technology giant known for its wide range of software products, including the Windows operating system, Office productivity suite, and cloud services like Azure. Microsoft also manufactures hardware, such as the Surface line of laptops and tablets, Xbox gaming consoles, and accessories.

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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


APU: An APU, or Accelerated Processing Unit, is a type of processor that combines a CPU and a GPU on a single chip. This type of processor is becoming increasingly popular in the computer industry due to its ability to provide both computing and graphics processing power in a single package. APUs are used in a variety of applications, from gaming PCs to high-end workstations. They are also used in embedded systems, such as those found in smartphones and tablets. The combination of CPU and GPU on a single chip allows for more efficient power consumption and better performance than traditional CPUs. Additionally, APUs are often used in conjunction with other components, such as RAM and storage, to create powerful and efficient systems.

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Compute Units: Compute Units (CUs) are a type of processor technology used in the computer industry. They are designed to provide high-performance computing capabilities for a variety of applications. CUs are typically used in graphics processing units (GPUs) and are responsible for the majority of the processing power in modern gaming systems. CUs are also used in other areas of the computer industry, such as artificial intelligence, machine learning, and data analysis. CUs are designed to be highly efficient and can provide significant performance gains over traditional CPUs. They are also capable of handling multiple tasks simultaneously, making them ideal for applications that require high levels of parallel processing.

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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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LLM: A Large Language Model (LLM) is a highly advanced artificial intelligence system, often based on complex architectures like GPT-3.5, designed to comprehend and produce human-like text on a massive scale. LLMs possess exceptional capabilities in various natural language understanding and generation tasks, including answering questions, generating creative content, and delivering context-aware responses to textual inputs. These models undergo extensive training on vast datasets to grasp the nuances of language, making them invaluable tools for applications like chatbots, content generation, and language translation.

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