Pure Storage Nabs NVIDIA DGX BasePOD Certification, Expands Enterprise AI Solutions

Pure Storage has enhanced its offerings to support artificial intelligence (AI) applications, becoming among the first enterprise data storage vendors to attain NVIDIA DGX BasePOD Certification for their AI Ready Infrastructure (AIRI). Additionally, Pure is now delivering, in partnership with Cisco, new Cisco Validated Designs for FlashStack for AI. Together, these enhancements enable enterprises to access data efficiently and reliably, crucial for deploying new AI applications and the foundation for scalable business outcomes.

Pure Storage has enhanced its offerings to support artificial intelligence (AI) applications, becoming among the first enterprise data storage vendors to attain NVIDIA DGX BasePOD Certification for their AI Ready Infrastructure (AIRI). Additionally, Pure is now delivering, in partnership with Cisco, new Cisco Validated Designs for FlashStack for AI. Together, these enhancements enable enterprises to access data efficiently and reliably, crucial for deploying new AI applications and the foundation for scalable business outcomes.

The company’s data storage platform is recognized as one of the most comprehensive in the market, providing unmatched efficiency and performance throughout the AI workflow, which includes data curation, model training, and inference. This is true for all stages of AI adoption across enterprises. Pure Storage has been powering leading AI initiatives worldwide, equipping customers with the ability to start AI projects at any scale and offering a data storage foundation that can expand with evolving needs.

AI-Ready Infrastructure Reference Model

One of the significant advancements in Pure Storage’s portfolio is the AI-Ready Infrastructure (AIRI) reference architecture as co-developed with NVIDIA. Since the introduction of FlashBlade in 2017 and AIRI in 2018, Pure Storage has been the leader in optimized AI storage. The AIRI, built on the NVIDIA DGX BasePOD reference architecture for AI and using the latest FlashBlade//S storage platform, allows for the easy and rapid scaling of AI deployments, enabling enterprises to focus on deriving insights instead of IT management.

Another key offering is FlashStack for AI, created in collaboration with Cisco, which aids IT teams in managing new AI application stacks and data pipelines. The Cisco Validated Designs for AI-accelerated FlashStack and NVIDIA AI Enterprise solutions provide a playbook for automation, allowing enterprises to deploy common AI models efficiently and securely.

Portworx by Pure Storage addresses the complexities of AI workloads in containerized environments. It enhances data science productivity by enabling quick setup of notebooks and pipelines, thus facilitating agility in model training and predictions. Portworx also provides data protection across various stages of the pipeline and contributes to cost savings by improving the utilization of storage resources in multi-cloud environments.

Keeping The AI Journey Flexible

As the demand for AI grows, Pure Storage has proactively delivered a high-performance, container-ready data storage platform suitable for the most advanced AI projects. This platform supports the development of large-scale AI training environments and deploying complex AI models, offering flexibility for customers’ AI journeys.

Enterprises are rapidly adopting AI to improve decision-making, operational efficiency, and scalability. However, the challenge of effectively integrating AI lies in establishing the proper data storage infrastructure. Such infrastructure must ensure data is immediately accessible, conforming to need, policy, and security, all while controlling costs. Pure Storage provides an efficient, high-performing solution that meets these AI demands. It is automated, resilient, and scalable, designed to adapt to changing needs and support a wide array of high-performance AI applications.

“Drivers of Change” Survey Results

Furthermore, in a collaborative effort with Wakefield Research, Pure Storage has unveiled a report titled “Drivers of Change: Meeting the Energy and Data Challenges of AI Adoption.” This publication underscores the critical nature of revisiting the data infrastructure to maximize the benefits of AI technologies, manage energy expenditure effectively, and align with corporate environmental objectives.

Highlights from the survey, which polled 500 IT buyers from firms employing over 500 people in the U.S. and Europe, include:

• A significant surge in computing power requirements linked to AI adoption, with 88 percent of adopters reporting a dramatic increase. Notably, nearly half have had to double, if not more, their computing capacity following AI integration.
• There is a lack of preparedness for the energy demands of AI, as 73 percent of IT buyers admitted they were not fully ready for the energy consumption AI entails.
• The acknowledgment that AI doesn’t only consume energy but also necessitates data management enhancements. Specific areas for upgrade include data management tools (48 percent), processes (46 percent), and storage infrastructure (46 percent).
• A near-universal trend (96 percent) towards IT infrastructure updates, with 29 percent of IT buyers indicating a complete overhaul is necessary due to AI.
• The impact of these upgrades on sustainability objectives, with 89 percent reporting difficulty in achieving ESG goals post-AI adoption. To address this, 60 percent of those who have adopted or plan to adopt AI technologies within a year intend to invest in more energy-efficient hardware to fulfill ESG commitments.

The rising adoption of AI across various sectors indicates a pivotal shift in business operations, yet many organizations encounter infrastructure inadequacies. These deficiencies present a significant barrier to leveraging AI’s full potential, particularly in supporting key corporate strategies and environmental targets. The survey reflects a common sentiment among IT professionals—that reducing the carbon footprint is a pressing concern, and optimizing IT infrastructure is essential for successfully adopting AI technologies.

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