AMD Instinct™ MI300X Accelerators

AMD Instinct™ MI300X accelerators are designed to deliver leadership performance for Generative AI workloads and HPC applications.

Name
AMD Instinct™ MI300X
Family
Instinct
Series
Instinct MI300 Series
Form Factor
Servers
Launch Date
12/06/2023
GPU Architecture
CDNA3
Lithography
TSMC 5nm | 6nm FinFET
Stream Processors
19,456
Matrix Cores
1216
Compute Units
304
Peak Engine Clock
2100 MHz
Peak Eight-bit Precision (FP8) Performance (E5M2, E4M3)
2.61 PFLOPs
Peak Eight-bit Precision (FP8) Performance with Structured Sparsity (E5M2, E4M3)
5.22 PFLOPs
Peak Half Precision (FP16) Performance
1.3 PFLOPs
Peak Half Precision (FP16) Performance with Structured Sparsity
2.61 PFLOPs
Peak Single Precision (TF32 Matrix) Performance
653.7 TFLOPs
Peak Single Precision (TF32) Performance with Structured Sparsity
1.3 PFLOPs
Peak Single Precision Matrix (FP32) Performance
163.4 TFLOPs
Peak Double Precision Matrix (FP64) Performance
163.4 TFLOPs
Peak Single Precision (FP32) Performance
163.4 TFLOPs
Peak Double Precision (FP64) Performance
81.7 TFLOPs
Peak INT8 Performance
2.6 POPs
Peak INT8 Performance with Structured Sparsity
5.22 POPs
Peak bfloat16
1.3 PFLOPs
Peak bfloat16 with Strutured Sparsity
2.61 PFLOPs
Transistor Count
153 Billion
External Power Connectors
54V UBB
Typical Board Power (TBP)
750W Peak
Last Level Cache (LLC)
256 MB
Dedicated Memory Size
192 GB
Dedicated Memory Type
HBM3
Infinity Cache
Yes
Memory Interface
8192-bit
Memory Clock
5.2 GHz
Peak Memory Bandwidth
5.3 TB/s
Memory ECC Support
Yes (Full-Chip)
GPU Form Factor
OAM Module
Bus Type
PCIe® 5.0 x16
Infinity Fabric™ Links
8
Peak Infinity Fabric™ Link Bandwidth
128 GB/s
Cooling
Passive OAM
Supported Technologies
AMD CDNA™ 3 Architecture , AMD ROCm™ - Ecosystem without Borders , AMD Infinity Architecture
RAS Support
Yes
Page Retirement
Yes
Page Avoidance
Yes
SR-IOV
Yes

Footnotes

MI300-17: Measurements conducted by AMD Performance Labs as of November 11th, 2023 on the AMD Instinct™ MI300X (750W) GPU designed with AMD CDNA™ 3 5nm | 6nm FinFET process technology at 2,100 MHz peak boost engine clock resulted in 653.7 TFLOPS peak theoretical TensorFloat-32 (TF32), 1307.4 TFLOPS peak theoretical half precision (FP16), 1307.4 TFLOPS peak theoretical Bfloat16 format precision (BF16), 2614.9 TFLOPS peak theoretical 8-bit precision (FP8), 2614.9 TOPs INT8 floating-point performance. The MI300X is expected to be able to take advantage of fine-grained structure sparsity providing an estimated 2x improvement in math efficiency resulting 1,307.4 TFLOPS peak theoretical TensorFloat-32 (TF32), 2,614.9 TFLOPS peak theoretical half precision (FP16), 2,614.9 TFLOPS peak theoretical Bfloat16 format precision (BF16), 5,229.8 TFLOPS peak theoretical 8-bit precision (FP8), 5,229.8 TOPs INT8 floating-point performance with sparsity. Published results on Nvidia H100 SXM (80GB) 700W GPU resulted in 989.4 TFLOPs peak TensorFloat-32 (TF32) with sparsity, 1,978.9 TFLOPS peak theoretical half precision (FP16) with sparsity, 1,978.9 TFLOPS peak theoretical Bfloat16 format precision (BF16) with sparsity, 3,957.8 TFLOPS peak theoretical 8-bit precision (FP8) with sparsity, 3,957.8 TOPs peak theoretical INT8 with sparsity floating-point performance. Nvidia H100 source: https://resources.nvidia.com/en-us-tensor-core.
MI300-18: Measurements conducted by AMD Performance Labs as of November 11th, 2023 on the AMD Instinct™ MI300X (750W) GPU designed with AMD CDNA™ 3 5nm | 6nm FinFET process technology at 2,100 MHz peak boost engine clock resulted in 163.4 TFLOPs peak theoretical double precision Matrix (FP64 Matrix), 81.7 TFLOPs peak theoretical double precision (FP64), 163.4 TFLOPs peak theoretical single precision Matrix (FP32 Matrix), 163.4 TFLOPs peak theoretical single precision (FP32), 653.7 TFLOPS peak theoretical TensorFloat-32 (TF32), 1307.4 TFLOPS peak theoretical half precision (FP16), 1307.4 TFLOPS peak theoretical Bfloat16 format precision (BF16), 2614.9 TFLOPS peak theoretical 8-bit precision (FP8), 2614.9 TOPs INT8 floating-point performance. Published results on Nvidia H100 SXM (80GB) GPU resulted in 66.9 TFLOPs peak theoretical double precision tensor (FP64 Tensor), 33.5 TFLOPs peak theoretical double precision (FP64), 66.9 TFLOPs peak theoretical single precision (FP32), 494.7 TFLOPs peak TensorFloat-32 (TF32)*, 989.4 TFLOPS peak theoretical half precision tensor (FP16 Tensor), 133.8 TFLOPS peak theoretical half precision (FP16), 989.4 TFLOPS peak theoretical Bfloat16 tensor format precision (BF16 Tensor), 133.8 TFLOPS peak theoretical Bfloat16 format precision (BF16), 1,978.9 TFLOPS peak theoretical 8-bit precision (FP8), 1,978.9 TOPs peak theoretical INT8 floating-point performance. Nvidia H100 source: https://resources.nvidia.com/en-us-tensor-core/ * Nvidia H100 GPUs don’t support FP32 Tensor.
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. https://nvdam.widen.net/s/nb5zzzsjdf/hpc-datasheet-sc23-h200-datasheet-3002446 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. https://resources.nvidia.com/en-us-tensor-core/nvidia-tensor-core-gpu-datasheet

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AMD Instinct™ MI300X Accelerators

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