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Scalability Guidelines for Deep Learning with High-Speed Object Storage
Executive summary Introduction
Introduction
Solution architecture Deep learning training performance and analysis Benchmark setup Conclusion References

Introduction

Home > Storage > ObjectScale and ECS > Industry Solutions and Verticals > Scalability Guidelines for Deep Learning with High-Speed Object Storage > Introduction

Introduction

  • DL is an area of AI that uses artificial neural networks to enable accurate pattern recognition of complex real-world patterns by computers. These new levels of innovation have applicability across nearly every industry vertical. Some of the early adopters include advanced research, precision medicine, high tech manufacturing, advanced driver assistance systems (ADAS), and autonomous driving. Building on these initial successes, AI initiatives are springing up in various business units, such as manufacturing, customer support, life sciences, marketing, and sales. Organizations are faced with numerous complex choices related to data, analytic skill sets, software stacks, analytic toolkits, and infrastructure components: each with significant implications on the time-to-market and the value associated with these initiatives.

    In such a complex environment, it is critical that organizations be able to rely on vendors that they trust. Over the last few years, Dell Technologies and NVIDIA have established a strong partnership to help organizations accelerate their AI initiatives. Our partnership is built on the philosophy of offering flexibility and informed choice across an extensive portfolio. Together our technologies provide the foundation for successful AI solutions that drive the development of advanced DL software frameworks, deliver massively parallel compute in the form of NVIDIA Graphic Processing Units (GPUs) for parallel model training, and scale-out object storage to support the concurrency, performance, and capacity requirements of unstructured image and video data sets.

    The digital era of business has been upon us for years now. As more businesses derive some portion of revenue from information-based products and services, the volume of data that must be created and stored increases. Simply storing data is not enough—successful digital initiatives require that organizations can leverage data as quickly as possible. As a result, all-flash storage architectures are increasing in popularity for object storage.

    Designed to support massive scale data environments, object storage delivers the scale that high-growth digital organizations require. With the integration of flash storage, these object storage environments can provide the performance to support data-intensive workloads while also supporting a wide variety of applications for consolidation.

    This document describes how customers can use Dell ECS EXF900 Object Storage to train an AI model with NVIDIA A100 GPUs. This new architecture gives customers more flexibility in how they deploy scalable, high-performance DL. The results of standard image classification training benchmark using TensorFlow are also included.