Amazon Web Services (AWS) is releasing Amazon Elastic Compute Cloud (Amazon EC2) DL1 instances, a new instance type designed for training machine learning models.
DL1 instances are powered by Gaudi accelerators from Habana Labs (an Intel company) to provide up to 40 per cent better price performance for training machine learning models than the latest GPU-powered Amazon EC2 instances, according to AWS.
With DL1 instances, customers can train their machine learning models faster and more cost effectively for use cases like natural language processing, object detection and classification, fraud detection, recommendation and personalisation engines, intelligent document processing, business forecasting, and more. DL1 instances are available on demand via a low-cost pay-as-you-go usage model with no upfront commitments.
DL1 instances feature up to eight Gaudi accelerators, 256 GB of high-bandwidth memory, 768 GB of system memory, 2nd generation Amazon custom Intel Xeon Scalable (Cascade Lake) processors, 400 Gbps of networking throughput, and up to 4 TB of local NVMe storage.
Customers can quickly and easily get started with DL1 instances using the included Habana SynapseAI SDK, which is integrated with leading machine learning frameworks (e.g. TensorFlow and PyTorch), helping customers to seamlessly migrate their existing machine learning models currently running on GPU-based or CPU-based instances onto DL1 instances, with minimal code changes.
Developers and data scientists can also start with reference models optimized for Gaudi accelerators available in Habana’s GitHub repository, which includes popular models for diverse applications, including image classification, object detection, natural language processing, and recommendation systems.
“The use of machine learning has skyrocketed. One of the challenges with training machine learning models, however, is that it is computationally intensive and can get expensive as customers refine and retrain their models,” said David Brown, vice president of Amazon EC2, at AWS.
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“AWS already has the broadest choice of powerful compute for any machine learning project or application. The addition of DL1 instances featuring Gaudi accelerators provides the most cost-effective alternative to GPU-based instances in the cloud to date. Their optimal combination of price and performance makes it possible for customers to reduce the cost to train, train more models, and innovate faster.”
Customers can launch DL1 instances using AWS Deep Learning AMIs or using Amazon Elastic Kubernetes Service (Amazon EKS) or Amazon Elastic Container Service (Amazon ECS) for containerized applications. For a more managed experience, customers can access DL1 instances through Amazon SageMaker, making it even easier and faster for developers and data scientists to build, train, and deploy machine learning models in the cloud and at the edge.
DL1 instances benefit from the AWS Nitro System, a collection of building blocks that offload many of the traditional virtualization functions to dedicated hardware and software to deliver high performance, high availability, and high security while also reducing virtualisation overhead.
