This resource is no longer available

Three Ways That AI Will Impact Your Data Management and Storage Strategy

Cover

I&O leaders selecting infrastructure for AI workloads involving machine learning and deep learning must comprehend the unique requirements of these emerging workloads. We analyze the impact of AI workloads on data infrastructure and outline best practices for storage selection and implementation.

Impacts

  • Different stages of AI workloads comprising compute intensive machine learning (ML) and deep neural networks (DNNs) have distinct input/output (IO) characteristics, requiring I&O leaders to deploy complementary storage architectures.
  • Unique requirements of AI and ML workloads will cause I&O leaders to re-evaluate their approach to storage selection and embrace new technology and deployment methods
  • The vendor ecosystem supporting ML workloads is nascent, but rapidly evolving, exacerbating vendor selection for I&O leaders.
Vendor:
IBM
Posted:
26 Feb 2019
Published:
26 Feb 2019
Format:
PDF
Type:
White Paper
Language:
English

This resource is no longer available.