AMD Instinct MI350 : Specifications, Architecture, Working, Differences & Its Applications

The AMD Instinct MI350 is a high-performance computing and AI accelerator. It is a successor to the Instinct MI300 series, which was announced by AMD in June 2025. Compared to its prior generation of GPU, it is focusing greatly on performance gains, mostly for generative AI. This provides up to 35 times the inferencing performance and four times the AI compute of its predecessor. This article elaborates on AMD Instinct MI350, its working, and its applications.

What is AMD Instinct MI350?

The AMD Instinct MI350 is a series or family of GPUs built on the 4th Gen CDNA architecture of AMD. It is designed for high-performance computing and data center-level Generative AI workloads. This GPU provides outstanding efficiency and performance for high-speed inference, complex scientific simulations, and massive AI model training. Thus, it features large HBM3E memory and advanced data types.

Additionally, this series can also include models such as the MI355X (liquid-cooled) and MI350X (air-cooled) for high-density deployments. This MI350 GPU includes HBM3E memory – 288GB, memory bandwidth – 8TB/s for the MI350X, with liquid-cooled options.

Specifications

The AMD Instinct MI350 data center GPU is built on the 4th Gen CDNA™ 4 architecture. This GPU has an advanced chiplet design, huge HBM3E memory & support for low-precision data formats. This series has two main products, the air-cooled MI350X & the liquid-cooled MI355X. The specifications of these GPUs include the following.

• It is built on 4th Gen CDNA™ 4 GPU Architecture.
• Process node is 3nm TSMC for XCDs and 6nm for IODs
• The Transistor Count for both is 185 billion.
• GPU Chiplets or XCDs – 8.
• Compute Units or CUs are 256.
• Its stream processors are 16,384.
• Matrix cores – 1,024
• Dedicated Memory is 288 GB HBM3E.
• Memory BW is 8 TB/s.
• Last Level Cache or LLC is 256 MB.
• Form factor is an OAM module.
• Cooling is air-cooled for MI350X and direct liquid-cooled for MI355X.
• Typical board power for MI350X is 1000 W (Peak) and for MI355X is 1400 W (Peak).

How does AMD Instinct MI350 Work?

The AMD Instinct MI350 GPU works with an advanced 4th Gen CDNA architecture. This uses a multi-chiplet design, high-speed Infinity Fabric interconnect, and massive HBM3E (High-Bandwidth Memory) to provide high-performance AI training, complex high-performance computing, and inference workloads. Thus, these components are synchronized by the open-source ROCm™ software stack to speed up workloads within data centers. This GPU supports the latest FP4 and FP6 data types with outstanding efficiency & speed for quick GPU-to-GPU communication in its UBB 2.0 (Universal Baseboard) platform.

AMD Instinct MI350 Architecture

The AMD Instinct MI350 uses the 4th Gen AMD CDNA™ or Compute DNA architecture. Its key features mainly include extended support for low-precision data types like FP4 and FP6 for better AI acceleration, huge HBM3E memory – 288GB, and 8TB/s of high bandwidth. In addition, it can also have better matrix engine throughput, native sparsity support & utilizes a high-performance based chiplet design. Thus, it is a significant advancement as compared to earlier generations for large-scale HPC and AI workloads.

AMD Instinct MI350 Architecture Components

The AMD Instinct MI350 architecture features various components, which is discussed below.

Accelerator Complex Dies or XCDs

The architecture includes specialized chiplets known as XCDs, which TSMC manufactures using its advanced 3nm process node. It integrates eight XCDs onto a package through two IODs (I/O dies) and HBM (High Bandwidth Memory). These chiplets include the core computational elements & performance-sensitive cache memory of the GPU. Thus, these are primary processing components, responsible for executing the required intensive calculations for HPC and AI workloads.

Compute Units

The MI350X & MI355X in the AMD Instinct MI350 architecture have a total of 256compute units. A CU is a basic building block that executes parallel processing for HPC and AI workloads. The CUs in this architecture are spread across eight separate XCDs, where each XCD includes 32 CUs.

Matrix Cores

This GPU includes specialized hardware units like matrix cores – 1,024, used for accelerating matrix multiplication & fused-multiply-add operations in machine learning and AI tasks. These are optimized for solid matrix multiplications, which are essential to generative AI and deep learning.

Vector & Matrix Pipelines

This architecture has extensively redesigned vector & matrix pipelines optimized for HPC and AI workloads. The 3D chiplet design is a key innovation that uses XCDs arranged on a 3nm process node; thus, it includes the compute units or CUs with their pipelines.

I/O Dies (IODs)

The MI350 series includes two repartitioned I/O dies built on a 6nm process. The IODs contain the system infrastructure and handle communication and memory traffic with improved efficiency and lower latency. The I/O dies in this architecture work as the base where the compute dies of GPUs are stacked. The design of AMD represents a major architectural shift from the MI300 series. Thus, decreases the number of IODs to enhance its efficiency and performance for HPC and AI workloads.

Memory Subsystem

The AMD Instinct MI350 architecture’s memory subsystem is designed for HPC and large-scale AI workloads to handle them very efficiently. Therefore, this system combines a massive 288GB of HBM3E memory capacity with 256MB of Infinity Cache to increase throughput and decrease latency.

High-Bandwidth Memory or HBM3E

The MI350 series GPU is equipped with HBM3E memory – 288GB across eight stacks. Thus, it provides a huge capacity for large models, which delivers memory bandwidth up to 8TB/s. This is an important generational improvement as compared to the MI300X. This improved memory subsystem is designed to meet the great demands of training & inference for massive HPC and generative AI models.

Infinity Cache™

This architecture includes an Infinity Cache – 256MB, which improves effective bandwidth and decreases memory latency by reducing right of entry to the exterior HBM. This architecture keeps its memory-side Infinity Cache with an enhanced shared cache – 256MB with 128 channels for power efficiency and higher memory bandwidth. It is arranged between the Infinity Fabric and HBM. Therefore, this shared memory cache improves performance by decreasing off-chip memory accesses. It is a main component of the new CDNA 4 architecture, which allows the MI350 series GPUs significant HPC and AI gains.

Interconnect & Scalability

The AMD Instinct MI350 architecture is designed for high-performance and scalable deployments through its higher interconnects & modular design. Thus, it uses a powerful chiplet design, the high-bandwidth and coherent Infinity Fabric. The interconnect allows direct and seamless GPU-to-GPU communication, which allows for scalability to large and multi-node data center clusters from a single server node.

This architecture uses two levels of Infinity Fabric interconnect to deliver high bandwidth & low latency: In addition, this architecture can also support scaling from a GPU to huge and rack-level deployments by combining hardware & software features.

AMD Infinity Fabric™

The Infinity Fabric in the architecture is a high-bandwidth external interconnect technology that delivers high-speed communication in the GPU & also in between GPUs within a GPU-to-GPU connectivity system. It connects the XCDs (accelerator complex dies) and IODs (I/O dies) for unified memory access. Thus, it allows high-throughput connections directly between various MI350 GPUs for large-scale HPC and AI workloads.

Infinity Fabric™ Links

In the AMD Instinct MI350 architecture, Infinity Fabric™ Links are the high-speed interconnects that allow multiple GPUs to communicate directly with each other. In a server platform, these links create a scalable, unified mesh network for ultra-fast, low-latency data exchange, which is critical for large-scale AI and high-performance computing (HPC) workloads. Every MI355X or MI350X accelerator utilizes seven Infinity Fabric links for multi-GPU systems to produce a completely connected mesh network by up to eight GPUs on a single UBB (universal baseboard).

Universal Baseboard or UBB 2.0

This is an industry-standard platform in the AMD Instinct MI350 architecture, which houses & connects eight OCP (Open Compute Project) accelerator modules (OAMs) like the MI350X or MI355X GPUs. This design is central to building high-performance AI and HPC systems that provide hardware interoperability and scalability. This series supports the OCP (Open Compute Project) UBB 2.0 standard by allowing for faultless upgrades from earlier MI300 series platforms.

AMD Instinct MI350 Software

The open-source AMD ROCm™ software stack is the primary software. It is an open choice to proprietary or AI platforms that provide the APIs, tools, and drivers to run HPC and AI workloads. This software stack ensures easy deployment and high performance of AI models, thus providing Day-0 support for ONNX Runtime, JAX, TensorFlow, and PyTorch frameworks. In addition, it supports higher inference and training features, which are necessary for large models like those utilized in generative AI.

AMD Instinct MI350 Series Vs AMD Instinct MI300 Series

The difference between the AMD Instinct MI350 Series and the AMD Instinct MI300 Series includes the following. Thus, the key differences include its architecture, memory capacity, bandwidth, and data types.

Advantages

The advantages of AMD Instinct MI350 include the following.

• The MI350 Series GPU provides significantly faster performance for AI workloads, particularly for complex generative AI models.
• It supports the new data types like FP6 and FP4, which are essential for optimizing energy efficiency and computational throughput for AI training & inference.
• It supports matrix sparsity to enhance efficiency and performance by optimizing training & inference by allowing for a sustainable level of AI solutions.
• The MI350X platform of this GPU boasts HBM3E memory – 288 GB with 8 TB/s of bandwidth for each accelerator and up to 2.3 TB of coherent, shared memory at the platform level, essential for massive AI models.
• In addition, the MI350 GPU is useful for next-gen Ethernet-based AI networking to promote huge scalability by allowing flexible and open-architecture deployments.
• An AMD Infinity Fabric™ mesh with high bandwidth can connect eight GPUs on a UBB 2.0 universal baseboard. Thus, it provides direct connectivity & bidirectional links – 153.6 GB/s for high-speed communication.

Disadvantages

The disadvantages of AMD Instinct MI350 include the following.

• This GPU has a less mature software ecosystem compared to the CUDA platform of NVIDIA.
• It has lower performance potentially in some compute-intensive workloads.
• Power draw is higher on liquid-cooled models like the MI355X (1,400W) and MI350X (1,000W).
• The MI350’s performance depends on the recently released ROCm 7.0 software stack.
• It does not support the NPS4 memory mode.

Applications

The applications of AMD Instinct MI350 include the following.

• The MI350 series GPU accelerates the development of massive generative AI models.
• In healthcare, this GPU enhances drug discovery and genomics research by speeding up data analysis.
• It provides outstanding performance and efficiency for large-scale and complex AI model training.
• It delivers lightning-fast inference, which is essential for real-time applications within financial trading and autonomous driving areas.
• This GPU runs complex scientific simulations & computational modeling. Thus, it is significant for research & development.
• It supports large-scale data processing and higher analytics to make it appropriate for a variety of industries.
• It optimizes network performance & customer experience in telecommunications by using superior data analytics.
• It improves algorithmic trading & risk assessment models in finance through higher inferencing capabilities.
• This GPU supports autonomous vehicle development by processing huge amounts of sensor data in real-time.

Conclusion:

Thus, this is an overview of the AMD Instinct MI350 series GPU, which is a powerhouse of an HPC and AI accelerator. It directly addresses key industry bottlenecks with a combination of exceptional performance gains, high-bandwidth memory, and an open and vendor-flexible software stack. The MI350 GPU for researchers and enterprises provides a compelling path in the direction of accelerated AI innovation through decreased vendor lock-in. Here is a question for you: What is AMD Instinct MI300 Series?