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AMD Instinct MI300X-192GB-HBM3 AI GPU Accelerator

Brand:
AMD

The AMD Instinct MI300X-192GB-HBM3 is a data-center OAM accelerator built for generative AI, large language models, machine learning, and HPC workloads. Based on AMD CDNA 3 architecture, it combines 192GB HBM3 memory, 5.3TB/s peak theoretical memory bandwidth, 304 GPU compute units, and up to 1.3 PFLOPS FP16/BF16 theoretical performance with a 750W peak board power. It is positioned within AMD’s Instinct MI300 Series as a high-memory accelerator for demanding AI and HPC deployments.

OVERVIEW

  • The AMD Instinct MI300X is a high-memory data-center OAM accelerator for generative AI, LLMs, HPC and large-model workloads. Need: maximize GPU memory capacity and bandwidth for models that exceed conventional accelerator memory footprints. Compatibility: OAM module with PCIe Gen 5 x16 host connectivity; use a qualified MI300X platform. Compare: MI300X provides 192GB HBM3, while newer MI325X increases capacity to 256GB HBM3E. 

USE CASES

  • Large language model inference – 192GB of HBM3 allows larger models and larger working datasets to remain on a single accelerator, reducing model partitioning requirements.
  • Generative AI training – High memory bandwidth and CDNA 3 compute resources support demanding AI training workloads.
  • LLM fine-tuning – Large on-package memory provides additional headroom for model weights, activations and training data.
  • AI inference serving – High memory capacity supports memory-intensive models and can help reduce the need for aggressive model quantization or multi-GPU partitioning in suitable workloads.
  • High-performance computing – FP64 and FP32 compute capabilities make the accelerator suitable for scientific and engineering workloads.
  • Machine learning – Provides GPU acceleration for supported ML frameworks running through the AMD ROCm software ecosystem.
  • Scientific simulation – Parallel GPU compute resources can accelerate supported computational science, simulation and numerical workloads.
  • Data analytics – High-bandwidth HBM3 supports applications requiring rapid movement of large datasets between compute resources.
  • Computer vision and image processing – GPU compute and supported media capabilities can accelerate suitable vision workloads.
  • Enterprise AI infrastructure – Can be deployed as part of qualified MI300X server and 8-GPU platform configurations for scalable data-center AI infrastructure.

KEY FEATURES

  • 192GB HBM3 memory – Provides substantial accelerator memory capacity for large AI models, datasets and HPC applications. 
  • 5.3TB/s peak theoretical memory bandwidth – Enables rapid movement of data between compute resources and HBM3 for bandwidth-intensive workloads. 
  • AMD CDNA 3 architecture – Provides a data-center-focused compute architecture optimized for AI and HPC acceleration. 
  • 304 GPU compute units – Provides substantial parallel processing resources for AI and scientific computing workloads.
  • 1,216 Matrix Cores – Accelerates matrix-oriented operations used extensively in AI and machine learning.
  • 19,456 stream processors – Provides large-scale parallel execution capacity for supported compute workloads.
  • Up to 1.3 PFLOPS FP16/BF16 theoretical performance – Provides high mathematical throughput for AI training and inference workloads. 
  • Up to 653.6 TFLOPS FP64 matrix performance – Provides substantial double-precision capability for HPC and scientific workloads. 
  • 256MB AMD Infinity Cache – Provides additional on-chip cache capacity to help feed compute resources efficiently.
  • 8192-bit memory interface – Provides a very wide HBM3 memory interface supporting the accelerator’s high bandwidth.
  • PCIe Gen 5 x16 – Provides high-speed host connectivity for qualified server and accelerator platforms. 
  • Up to 7 Infinity Fabric links – Provides high-speed GPU-to-GPU connectivity for supported multi-GPU configurations.
  • 128GB/s per Infinity Fabric link – Supports high-bandwidth accelerator communication in compatible platform designs. 
  • Full-chip ECC memory – Provides error-correction capability for improved data integrity in enterprise and HPC environments.
  • SR-IOV support with up to 8 partitions – Enables supported virtualization and accelerator-sharing configurations.
  • Passive OAM form factor – Allows integration into qualified high-density accelerator platforms with platform-level cooling.

TECHNICAL SPECIFICATIONS

  • Brand: AMD
  • Product family: AMD Instinct MI300 Series
  • Accelerator: MI300X
  • SKU: MI300X-192GB-HBM3
  • Product type: Data-center GPU accelerator
  • Architecture: AMD CDNA 3
  • Form factor: OAM module
  • GPU compute units: 304
  • Matrix cores: 1,216
  • Stream processors: 19,456
  • Peak engine clock: Up to 2,100MHz
  • Memory capacity: 192GB
  • Memory type: HBM3
  • Memory interface: 8192-bit
  • Memory clock/data rate: Up to 5.2 GT/s
  • Peak theoretical memory bandwidth: 5.3TB/s
  • AMD Infinity Cache: 256MB
  • FP64 vector: 81.7 TFLOPS
  • FP64 matrix: 163.4 TFLOPS
  • FP32: 163.4 TFLOPS
  • TF32: 653.7 TFLOPS
  • FP16: 1.307 PFLOPS
  • BF16: 1.307 PFLOPS
  • FP8: 2.615 PFLOPS
  • INT8: 2.615 POPS
  • FP16/BF16 with structured sparsity: 2.615 PFLOPS
  • FP8/INT8 with structured sparsity: 5.23 PFLOPS
  • Host interface: PCIe Gen 5 x16
  • Host I/O bandwidth: 128GB/s
  • Infinity Fabric links: Up to 7
  • Infinity Fabric bandwidth: 128GB/s per link
  • GPU peer-to-peer transport: Up to 896GB/s aggregate theoretical in supported configurations
  • ECC: Full-chip ECC
  • RAS: Yes
  • Page retirement: Yes
  • Page avoidance: Yes
  • SR-IOV: Yes, up to 8 partitions

Why Choose This Product?

  • 192GB HBM3 per accelerator for memory-intensive AI and HPC workloads
  • 5.3TB/s memory bandwidth for high-throughput data processing
  • CDNA 3 architecture purpose-built for data-center compute acceleration
  • 304 compute units and 1,216 Matrix Cores for highly parallel workloads
  • Strong FP64 capability for scientific and engineering computing
  • PCIe Gen 5 x16 connectivity for high-speed host communication
  • Infinity Fabric connectivity for scalable multi-GPU deployments
  • ECC and RAS features for enterprise and HPC reliability requirements

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