Skip to content

AWS EC2 P4d Instances: High-Performance GPU Compute for ML and HPC

Amazon Web Services (AWS) offers a range of EC2 instances optimized for various workloads. Among these, the P4d instances stand out as high-performance solutions equipped with NVIDIA A100 Tensor Core GPUs, making them ideal for machine learning (ML) training and high-performance computing (HPC) applications.

What Are P4d Instances?

P4d instances are GPU-powered EC2 instances designed to deliver high performance for ML training and HPC applications. They are equipped with NVIDIA A100 Tensor Core GPUs, offering significant improvements over previous generations in terms of performance and efficiency. These instances are ideal for applications requiring high-throughput compute and low-latency networking.

Key Features

  • GPU: 8 × NVIDIA A100 Tensor Core GPUs with 40 GB HBM2 memory each.
  • vCPUs: 96 Intel Xeon Platinum 8175M CPUs.
  • Memory: 1.1 TB of system memory.
  • Storage: 8 TB of local NVMe SSD storage with up to 16 GB/s read throughput.
  • Networking: 400 Gbps Elastic Fabric Adapter (EFA) with support for GPUDirect RDMA.
  • Availability: Available in multiple AWS regions, including Europe (Frankfurt, London), Asia Pacific (Tokyo, Malaysia), and Canada (Central) (aws.amazon.com).

Performance Enhancements

Compared to previous generations, P4d instances offer:

  • Up to 2.5× better deep learning performance: Enhanced processing power for demanding applications.
  • High-throughput networking: 400 Gbps bandwidth with EFA for scalable ML and HPC workloads.
  • Low-latency GPU-to-GPU communication: Enabled by GPUDirect RDMA technology.

Ideal Use Cases

P4d instances are well-suited for:

  • Machine Learning Training: Training large-scale models for applications like natural language processing, image classification, and recommendation systems.
  • High-Performance Computing: Running simulations and analyses in fields such as genomics, climate modeling, and financial modeling.
  • Distributed ML Workloads: Scaling ML training across multiple nodes using EC2 UltraClusters.

Cost Efficiency

P4d instances offer a competitive price-to-performance ratio, delivering up to 60% lower cost to train ML models compared to previous-generation P3 instances. Additionally, they are available as Spot Instances, allowing users to take advantage of unused EC2 capacity at significant discounts.

Conclusion

AWS EC2 P4d instances provide high-performance GPU compute for ML and HPC applications. With the latest NVIDIA A100 Tensor Core GPUs, large memory capacity, and high-throughput networking, P4d instances offer a robust solution for enterprises and researchers seeking to scale their GPU workloads.