AMD Delivers Leadership Portfolio of Data Center AI Solutions with AMD Instinct MI300 Series
AMD announced the availability of the AMD Instinct™ MI300X accelerators – with industry leading memory bandwidth for generative AI1 and leadership performance for large language model (LLM) training and inferencing – as well as the AMD Instinct™ MI300A accelerated processing unit (APU) – combining the latest AMD CDNA™ 3 architecture and “Zen 4” CPUs to deliver breakthrough performance for HPC and AI workloads.
“AMD Instinct MI300 Series accelerators are designed with our most advanced technologies, delivering leadership performance, and will be in large scale cloud and enterprise deployments,” said Victor Peng, president, AMD. “By leveraging our leadership hardware, software and open ecosystem approach, cloud providers, OEMs and ODMs are bringing to market technologies that empower enterprises to adopt and deploy AI-powered solutions.”
MD Instinct MI300X
AMD Instinct MI300X accelerators are powered by the new AMD CDNA 3 architecture. When compared to previous generation AMD Instinct MI250X accelerators, MI300X delivers nearly 40% more compute units2, 1.5x more memory capacity, 1.7x more peak theoretical memory bandwidth3 as well as support for new math formats such as FP8 and sparsity; all geared towards AI and HPC workloads.
Today’s LLMs continue to increase in size and complexity, requiring massive amounts of memory and compute. AMD Instinct MI300X accelerators feature a best-in-class 192 GB of HBM3 memory capacity as well as 5.3 TB/s peak memory bandwidth2 to deliver the performance needed for increasingly demanding AI workloads. The AMD Instinct Platform is a leadership generative AI platform built on an industry standard OCP design with eight MI300X accelerators to offer an industry leading 1.5TB of HBM3 memory capacity. The AMD Instinct Platform’s industry standard design allows OEM partners to design-in MI300X accelerators into existing AI offerings and simplify deployment and accelerate adoption of AMD Instinct accelerator-based servers.
Compared to the Nvidia H100 HGX, the AMD Instinct Platform can offer a throughput increase of up to 1.6x when running inference on LLMs like BLOOM 176B4 and is the only option on the market capable of running inference for a 70B parameter model, like Llama2, on a single MI300X accelerator; simplifying enterprise-class LLM deployments and enabling outstanding TCO.
AMD Instinct MI300A
The AMD Instinct MI300A APUs, the world’s first data center APU for HPC and AI, leverage 3D packaging and the 4th Gen AMD Infinity Architecture to deliver leadership performance on critical workloads sitting at the convergence of HPC and AI. MI300A APUs combine high-performance AMD CDNA 3 GPU cores, the latest AMD “Zen 4” x86-based CPU cores and 128GB of next-generation HBM3 memory, to deliver ~1.9x the performance-per-watt on FP32 HPC and AI workloads, compared to previous gen AMD Instinct MI250X5.
Energy efficiency is of utmost importance for the HPC and AI communities, however these workloads are extremely data- and resource-intensive. AMD Instinct MI300A APUs benefit from integrating CPU and GPU cores on a single package delivering a highly efficient platform while also providing the compute performance to accelerate training the latest AI models. AMD is setting the pace of innovation in energy efficiency with the company’s 30×25 goal, aiming to deliver a 30x energy efficiency improvement in server processors and accelerators for AI-training and HPC from 2020-20256.
The APU advantage means that AMD Instinct MI300A APUs feature unified memory and cache resources giving customers an easily programmable GPU platform, highly performant compute, fast AI training and impressive energy efficiency to power the most demanding HPC and AI workloads.
Product Specifications
| AMD Instinct™ | Architecture | GPU CUs | CPU Cores | Memory | Memory Bandwidth (Peak theoretical) | Process Node | 3D Packaging w/ 4th Gen AMD Infinity Architecture |
| MI300A | AMD CDNA™ 3 | 228 | 24 “Zen 4” | 128GB HBM3 | 5.3 TB/s | 5nm / 6nm | Yes |
| MI300X | AMD CDNA™ 3 | 304 | N/A | 192GB HBM3 | 5.3 TB/s | 5nm / 6nm | Yes |
Available at all major platform providers – Supermicro, Gigabyte, Asrock, Tyan, Asus.
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1 MI300-05A: Calculations conducted by AMD Performance Labs as of November 17, 2023, for the AMD Instinct™ MI300X OAM accelerator 750W (192 GB HBM3) designed with AMD CDNA™ 3 5nm FinFet process technology resulted in 192 GB HBM3 memory capacity and 5.325 TFLOPS peak theoretical memory bandwidth performance. MI300X memory bus interface is 8,192 and memory data rate is 5.2 Gbps for total peak memory bandwidth of 5.325 TB/s (8,192 bits memory bus interface * 5.2 Gbps memory data rate/8).
The highest published results on the NVidia Hopper H200 (141GB) SXM GPU accelerator resulted in 141GB HBM3e memory capacity and 4.8 TB/s GPU memory bandwidth performance.
The highest published results on the NVidia Hopper H100 (80GB) SXM5 GPU accelerator resulted in 80GB HBM3 memory capacity and 3.35 TB/s GPU memory bandwidth performance.
2 MI300-15: The AMD Instinct™ MI300X (750W) accelerator has 304 compute units (CUs), 19,456 stream cores, and 1,216 Matrix cores.
The AMD Instinct™ MI250 (560W) accelerators have 208 compute units (CUs), 13,312 stream cores, and 832 Matrix cores.
The AMD Instinct™ MI250X (500W/560W) accelerators have 220 compute units (CUs), 14,080 stream cores, and 880 Matrix cores.
3 MI300-13: Calculations conducted by AMD Performance Labs as of November 7, 2023, for the AMD Instinct™ MI300X OAM accelerator 750W (192 GB HBM3) designed with AMD CDNA™ 3 5nm FinFet process technology resulted in 192 GB HBM3 memory capacity and 5.325 TFLOPS peak theoretical memory bandwidth performance. MI300X memory bus interface is 8,192 (1024 bits x 8 die) and memory data rate is 5.2 Gbps for total peak memory bandwidth of 5.325 TB/s (8,192 bits memory bus interface * 5.2 Gbps memory data rate/8).
The AMD Instinct™ MI250 (500W) / MI250X (560W) OAM accelerators (128 GB HBM2e) designed with AMD CDNA™ 2 6nm FinFet process technology resulted in 128 GB HBM3 memory capacity and 3.277 TFLOPS peak theoretical memory bandwidth performance. MI250/MI250X memory bus interface is 8,192 (4,096 bits times 2 die) and memory data rate is 3.20 Gbps for total memory bandwidth of 3.277 TB/s ((3.20 Gbps*(4,096 bits*2))/8).
4 MI300-34: Token generation throughput using DeepSpeed Inference with the Bloom-176b model with an input sequence length of 1948 tokens, and output sequence length of 100 tokens, and a batch size tuned to yield the highest throughput on each system comparison based on AMD internal testing using custom docker container for each system as of 11/17/2023.
Configurations:
2P Intel Xeon Platinum 8480C CPU powered server with 8x AMD Instinct™ MI300X 192GB 750W GPUs, pre-release build of ROCm™ 6.0, Ubuntu 22.04.2.
Vs.
An Nvidia DGX H100 with 2x Intel Xeon Platinum 8480CL Processors, 8x Nvidia H100 80GB 700W GPUs, CUDA 12.0, Ubuntu 22.04.3.
8 GPUs on each system were used in this test.
Server manufacturers may vary configurations, yielding different results. Performance may vary based on use of latest drivers and optimizations.
5 MI300-23: Calculations conducted by AMD Performance Labs as of Nov 16, 2023, for the AMD Instinct™ MI300X (192GB HBM3 OAM Module) 750W accelerator designed with AMD CDNA™ 3 5nm | 6nm FinFET process technology at 2,100 MHz peak boost engine clock resulted in 163.43 TFLOPS peak theoretical single precision (FP32) floating-point performance.
The AMD Instinct™ MI300A (128GB HBM3 APU) 760W accelerator designed with AMD CDNA™ 3 5nm | 6nm FinFET process technology at 2,100 MHz peak boost engine clock resulted in 122.573 TFLOPS peak theoretical single precision (FP32) floating-point performance.
The AMD Instinct™ MI250X (128GB HBM2e OAM module) 560W accelerator designed with AMD CDNA™ 2 6nm FinFET process technology at 1,700 MHz peak boost engine clock resulted in 47.9 TFLOPS peak theoretical single precision (FP32) floating-point performance.
6 Includes AMD high-performance CPU and GPU accelerators used for AI training and high-performance computing in a 4-Accelerator, CPU-hosted configuration. Goal calculations are based on performance scores as measured by standard performance metrics (HPC: Linpack DGEMM kernel FLOPS with 4k matrix size. AI training: lower precision training-focused floating-point math GEMM kernels such as FP16 or BF16 FLOPS operating on 4k matrices) divided by the rated power consumption of a representative accelerated compute node, including the CPU host + memory and 4 GPU accelerators.