Today at the 2018 International Supercomputing Conference in Frankfurt, Germany, global supercomputer leader Cray Inc. announced it is accelerating and simplifying its customers’ path to value from artificial intelligence (AI). The company is introducing the Cray Urika-CS AI and Analytics software suite for the Cray CS series and new Cray Accel AI reference configurations to help IT and AI teams.
A typical AI workflow spans data preparation using analytic tools through to model development and model deployment using AI tools. It can be time consuming and resource intensive to implement. The Cray Urika-CS AI and Analytics suite and new Cray Accel AI reference configurations join key tools and system configuration guidance to simplify the implementation of AI. The Cray Urika-CS AI and Analytics suite makes the most popular AI and analytics tools and frameworks readily available on all GPU- and CPU-based Cray CS series systems, including TensorFlow, BigDL, Apache Spark, Dask, Jupyter Notebook and TensorBoard.
The Cray Urika-CS AI and Analytics suite is optimized for and supported on the Cray CS series cluster supercomputers and brings analytics and artificial intelligence capabilities to existing HPC and emerging AI environments. Combined with the Cray Urika-XC AI and Analytics suite for the Cray XC series supercomputers, these powerful tools will now be available across Cray’s portfolio of computing solutions.
“Today’s organizations are faced with a daunting task: to quickly implement and integrate new applications that take advantage of the latest advancements in Artificial Intelligence,” said Mike Leone, senior analyst at ESG. “Successful AI application deployments require that teams overcome numerous hurdles, including infrastructure complexity and a constantly evolving technology landscape. There’s an increasing demand for a simplified way to make AI workflows more efficient and sustainable by leveraging a purpose-built system that simultaneously addresses the integration, performance, and support challenges brought on by AI.”
Additionally, Cray is introducing updated Cray Accel AI reference configurations, which are designed to give IT teams the ability to quickly meet the needs of AI teams implementing the AI workflow. The new Cray Accel AI reference configurations bring together Cray CS series systems, Cray ClusterStor high-performance storage and Cray Urika-CS AI and Analytics software to provide system configuration guidance to IT organizations that are selecting and implementing infrastructure to meet AI team requirements. Updated and expanded Cray Accel AI configurations are available in both a “Prototype” and “Production” configuration.
“Today’s AI solutions are either too narrowly focused on deep learning or too ad hoc in their design approaches to meet the needs of AI and IT teams developing and delivering AI applications,” said Fred Kohout, Cray’s senior vice president of products and chief marketing officer. “Cray is taking the pain and guesswork out of AI deployments so companies can get to business outcomes faster.”
Cray Urika-CS AI and Analytics Suite
The Cray Urika-CS AI and Analytics suite addresses four key issues facing AI and IT teams:
Access to a range of tools for the AI workflow: Data preparation and model development require different frameworks and tools. The Cray Urika-CS suite includes popular data analytics environments (Apache Spark and Dask), data science libraries for Python (Anaconda distribution), machine and deep learning frameworks (TensorFlow and BigDL) and interactive environments to visualize data science work (Jupyter Notebook and TensorBoard).
Simplified and distributed model training with TensorFlow: Setting up and using TensorFlow for distributed model training can be laborious. The Cray Urika-CS suite includes the Cray Distributed Training Framework – originally developed for Cray XC Series supercomputers running Cray’s Urika-XC AI and Analytics suite – simplifies and reduces the time associated with configuring and running TensorFlow-based distributed neural network training and can reduce the time required to train deep learning models by leveraging the supercomputing infrastructure available on Cray CS series systems.
Reduced time and complexity for the setup and maintenance of AI and Analytics environments: Setting up and maintaining a consistent environment for users can be a time-consuming, seemingly never-ending task. With the Cray Urika-CS suite, Cray provides an integrated and tested suite of tools – ready to run on Cray CS series systems – that eliminate the time required by IT teams to download, install, test, debug and distribute myriad AI tools and frameworks to users.
Support for open-source tools and frameworks: With the Cray Urika-CS suite, Cray is the single point of contact for support and updates.
Cray Accel AI reference configurations
The new Cray Accel AI reference configurations are designed to simplify the choices for IT teams deploying infrastructure for the AI workflow:
Prototype configuration for small AI teams: a single-rack configuration that includes a combination of Cray’s CS500 CPU nodes and CS-Storm 500NX GPU-accelerated nodes for data preparation, analytics, machine learning and deep learning with Cray ClusterStor L300F flash and L300N disk storage solutions for performant cost-effective data pools. The Cray Urika-CS suite provides the software to best utilize this heterogeneous compute and hybrid storage configuration.
Production configuration for larger or growing teams: A multi-rack configuration with separate racks for CPU-based compute, GPU-based compute and storage that allows for flexible scaling as teams grow and needs evolve.
The combination of systems and software has been designed so that IT teams can enable their AI users to focus on insight and results rather than system and tools.