AW

AWS Trainium2

NeuronCore-v3 2024
FP32
181.0
TFLOPS
VRAM
96 GB
Bandwidth
2.9 TB/s
memory
NeuronCore-v3
8

Overview

AWS Trainium2 is Amazon's third-generation AI training and inference accelerator, and the chip behind Trn2 instances and Trn2 UltraServers. Each chip carries eight NeuronCore-v3 delivering 1,299 FP8 TFLOPS, 667 TFLOPS across BF16, FP16 and TF32, and 181 FP32 TFLOPS, with 96 GiB of device memory at 2.9 TB/s and 224 MiB of software-managed on-chip SBUF scratchpad. Chip-to-chip traffic runs over NeuronLink-v3 at 1.28 TB/s per chip, and 16 dedicated CC-Cores orchestrate collective communication so that reductions do not consume compute cores. AWS publishes a sparse figure of 2,563 TFLOPS spanning FP8, FP16, BF16 and TF32; note that this is 1.97x the dense FP8 rate but 3.84x the dense BF16 rate, so it does not behave like conventional 2:4 structured sparsity and should not be read as a simple doubling. AWS publishes no TDP and does not name the process node or the memory generation for this chip.

Performance Metrics

Peak theoretical throughput by precision type

PrecisionBitsPeak TFLOPS
FP8 8 1299.0
FP16 16 667.0
BF16 16 667.0
TF32 32 667.0
FP32 32 181.0

Power Specifications

TDP

--

Max Power

--

Power Connector

PCIe Slot

Cooling

Air

Memory Specifications

Capacity

96 GB

Type

--

Bandwidth

2900 GB/s

Interface

--

Hardware & Design

Form Factor

--

Architecture

NeuronCore-v3

Process Node

--

Launch Year

2024

Variant

Standard

Market Segment

Professional

Full Specifications

Compute Engine
NeuronCore-v3 8
Memory
VRAM 96 GB
Bandwidth 2.9 TB/s
On-Die SRAM 224 MB
Interconnect & I/O
GPU-to-GPU NeuronLink-v3
Interconnect Bandwidth 1.3 TB/s
Power & Thermal
Enterprise Features
Sparsity (2:4) Yes
General
Architecture NeuronCore-v3
Launch Year 2024

Documentation & Resources

Common Use Cases

General Compute AI/ML Workloads Data Processing

The AWS Trainium2 is optimized for high-performance computing tasks with NeuronCore-v3 architecture delivering 181 TFLOPS of compute power.

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