By using purpose-built acceleration, the DL2q instances deliver high throughput at a low cost. For example, DL2q instances deliver 100k ResNet50 images for less than $0.0017 or 100k BERT sequences for less than $0.0076.

DL2q instances and Qualcomm Apps and Platform SDK support leading ML frameworks such as TensorFlow and PyTorch, enabling you to continue using your preferred ML workflows. The Qualcomm Apps SDK also includes tools to enable easy porting and deployment of pre-trained models to DL2q instances while achieving the performance benefits of a purpose-built AI inference accelerator.  

The same Qualcomm AI stack runs on Qualcomm edge devices and DL2q instances. This provides customers with a consistent developer experience, with a unified API across their cloud and edge development environments. So you can use DL2q instances to develop and validate AI solutions for smartphones, autonomous driving, personal compute, and extended reality headsets.

DL2q instances feature 8 Qualcomm AI 100 accelerators with 16 GiB of memory per accelerator, 768 GiB of system memory, 2nd Generation Intel Xeon Scalable Processors, and 100 Gbps of network bandwidth.

You can get started with DL2q instances using the Qualcomm Cloud AI Platform SDK. The SDK is comprised of kernel drivers for different OSs, user-space utilities, firmware, libraries, and validation tools. The Cloud AI Apps SDK contains the libraries and tools to help application developers and framework developers to interface with Qualcomm AI 100 accelerators. These SDKs are integrated with leading frameworks such as TensorFlow and PyTorch.

DL2q instances are built on the AWS Nitro System, which is a rich collection of building blocks that offloads many of the traditional virtualization functions to dedicated hardware and software to deliver high performance, high availability, and high security while also reducing virtualization overhead.