Analyst(s): Steven Dickens
Publication Date: October 15, 2024
HPE took the opportunity presented by its AI leadership day to introduce a fanless, direct liquid cooling system. This announcement represents a significant advancement in energy-efficient AI infrastructure, at a time when data centers are coming under strain. However, competition from Lenovo’s Neptune systems and other players such as Dell and Supermicro is intensifying. HPE’s highly curated and opinionated approach addresses the key concern for enterprises – time to value.
What is Covered in this Article:
- HPE’s fanless direct liquid cooling system and its impact on AI infrastructure.
- Competition from Lenovo’s Neptune systems and other market players.
- The trend toward pre-integrated AI solutions and simplified hybrid cloud deployments.
- Regulatory influences on data sovereignty and energy consumption in AI infrastructure.
- How rising GenAI demands may drive cost-efficient alternatives and shape the competitive landscape.
The News: HPE introduced the industry’s first 100% fanless direct liquid cooling system designed to increase energy efficiency and reduce operational costs for AI workloads. This innovation aligns with HPE’s broader AI strategy, which includes a co-engineered system with NVIDIA to streamline deployment and support hybrid cloud AI infrastructures.
Will HPE’s Cooling Revolution Truly Redefine AI Infrastructure Efficiency?
Analyst Take: HPE has a storied history as an innovator and this was further cemented when HPE acquired Cray in May 2019 for approximately $1.3 billion, aiming to enhance its high-performance computing (HPC) and AI capabilities. This has proved to be yet another acquisition where in hindsight Antonio Neri got it right. The acquisition allowed HPE to integrate Cray’s supercomputing technologies into its portfolio, strengthening its position in the rapidly growing HPC market.
Going down memory lane, Seymour Cray, a legendary pioneer in supercomputing, is best known for his innovative designs that pushed the boundaries of performance and efficiency. His groundbreaking early work on liquid-cooled systems, particularly the Cray-2 (introduced in 1985), revolutionized high-performance computing. The Cray-2 was the world’s fastest supercomputer at the time, utilizing liquid immersion cooling to dissipate the enormous heat generated by its densely packed, high-speed components. The entire system was submerged in a special non-conductive fluid, Fluorinert, developed by 3M, allowing for efficient heat management and enabling higher processing speeds. This engineering has laid the foundation for where HPE is today.
This hard, truly impressive engineering approach laid the groundwork for modern liquid immersion cooling systems, now used in high-density data centers and advanced AI infrastructure. Liquid cooling innovation, as seen in the Cray-2, has evolved to support the increased demands of current supercomputing and AI workloads, offering significant energy savings and improved performance over traditional air-cooled methods. Cray’s innovations continue to influence cooling technologies in high-performance computing today.
Visiting HPE’s facility in Wisconsin was an opportunity to see cutting-edge technology in action and up close. Known for its long history with Cray systems, this facility is now home to some of the most advanced AI hardware in the world, including HPE’s fanless direct liquid cooling architecture.
Walking through the manufacturing floor, it became clear that HPE is not just building hardware; it’s crafting systems designed for the future of AI workloads. Seeing Cray systems still at the core of HPE’s supercomputing strategy was fascinating. Their integration into modern infrastructure is a testament to how the legacy of Seymour Cray has evolved in response to today’s demands. The facility itself is impressive—one of the largest direct liquid cooling sites globally, purpose-built for this new generation of AI computing.
One thing that struck me during the tour was HPE’s focus on energy efficiency. It’s no secret to anyone tracking the datacenter space that AI systems require massive computational power, which in turn generates significant heat. Cooling has always been a challenge, and HPE has tackled this head-on by introducing the 100% fanless direct liquid cooling architecture. Unlike traditional systems that rely on fans to dissipate heat, HPE’s approach leverages Direct Liquid Cooling to keep temperatures in check. The benefits are clear—reduced energy consumption, lower operational costs, and an architecture designed to scale with the needs of generative AI (GenAI).
At the heart of this innovation is a desire to reduce both energy use and environmental impact. It’s not just about creating faster systems but about ensuring they are sustainable in the long term. During the event, I learned that HPE’s liquid cooling uses over 18K tons of chilled water, a significant amount, but one that allows these systems to run reliably at scale. There’s no denying that this is where the future of AI hardware is heading—solutions that deliver high performance without compromising energy efficiency.
One particularly exciting development is HPE’s co-engineered systems with NVIDIA. AI computing is complex, and enterprises are looking for simplicity in deploying these systems. The collaboration between HPE and NVIDIA is designed to address this. It’s not just about providing the hardware; it’s about offering an integrated solution that is operationally efficient. HPE has built what can only be described as a ‘plug-and-play’ solution for AI workloads. In fact, with just three clicks, these systems can be fully deployed.
This seamless operation is a critical differentiator. For companies, particularly those moving into large-scale AI operations, the ability to deploy systems quickly without technical complexity is invaluable. The Cray systems, now co-engineered with NVIDIA’s AI accelerators, offer the performance needed for large language models and data-intensive tasks, while maintaining simplicity. It was clear from conversations with the HPE team that this partnership is a key part of their AI strategy going forward.
The three-click deployment process isn’t just a headline feature; it has real-world implications. Enterprises often face delays in getting AI systems up and running. By reducing the complexity of setup and integrating NVIDIA’s software with HPE’s AI servers, this solution addresses one of the biggest pain points in the industry. Moreover, HPE’s GreenLake platform plays a crucial role in supporting hybrid cloud AI workloads, providing the necessary infrastructure to scale AI without the challenges of managing a complex IT estate.
Another key point that emerged during my visit was how this technology caters to different customer segments. Whether it’s hyperscalers building their own AI models or sovereigns investing in AI infrastructure for national security, HPE’s approach seems tailored to specific needs. For hyperscalers, the large, direct liquid-cooled systems provide the foundation for massive AI model training, ensuring reliability at scale. For enterprises, the focus is on ease of use and rapid deployment—critical as AI moves from experimental stages to full-scale adoption.
HPE’s facility in Wisconsin embodies the company’s long-term vision. It’s not just about creating powerful systems, but about delivering a curated experience that meets the needs of today’s AI-driven enterprises. As AI continues to introduce disruptions across industries, the ability to simplify deployment while ensuring performance is going to be a key competitive advantage.
In conclusion, what I saw at HPE’s facility was more than just impressive hardware—it was a glimpse into the future of AI infrastructure. The blend of legacy expertise from Cray, combined with HPE’s innovative cooling solutions and its partnership with NVIDIA, positions the company as a leader in the AI space. The fanless direct liquid cooling architecture and the simplicity of three-click deployment are not just technological milestones, they represent a shift in how enterprises can leverage AI at scale. HPE has clearly positioned itself to meet the growing demands of this new era in computing, and I look forward to seeing how these innovations continue to evolve.
What to Watch:
- HPE’s 100% fanless direct liquid cooling system is a major step in energy-efficient AI infrastructure, but competition is intensifying, especially with Lenovo’s 6th Generation Neptune systems. Lenovo’s platform, with integrated direct liquid cooling and a sustainability focus, is becoming an industry benchmark. As AI adoption scales, enterprises will prioritize energy efficiency alongside performance, making Lenovo’s Neptune a strong alternative.
- HPE’s NVIDIA partnership reflects the trend toward pre-integrated AI solutions, yet competitors like Dell and Supermicro are also simplifying hybrid cloud deployments. These rivals may limit HPE’s market growth if they offer similar three-click solutions.
- Industry dynamics, including regulatory focus on data sovereignty and energy consumption, could shift demand toward providers with robust compliance and sustainability frameworks. Competitors such as Oracle and AWS may influence HPE’s AI cloud market share.
- As GenAI drives higher energy demands, cost-efficient liquid-cooled systems from Lenovo, NVIDIA, and Intel could challenge HPE. Competitors such as Cisco, focusing on hybrid cloud AI, may further constrain HPE’s growth by targeting niche workloads. Monitoring these trends will reveal how HPE’s innovations hold up in this evolving market.
For more details on how HPE is positioning itself to take advantage of the AI hypercycle, check out the details from their recent AI Leadership day.
Disclosure: The Futurum Group is a research and advisory firm that engages or has engaged in research, analysis, and advisory services with many technology companies, including those mentioned in this article. The author does not hold any equity positions with any company mentioned in this article.
Analysis and opinions expressed herein are specific to the analyst individually and data and other information that might have been provided for validation, not those of The Futurum Group as a whole.
Other insights from The Futurum Group:
HPE Unveils NVIDIA AI Computing by HPE: Enterprise AI Ascends
How Does HPE Private Cloud AI Enable One-Click Deployment of GenAI Assistants?
Showtime #2: HPE, Pure Accelerate and FinOPsX – Infrastructure Matters, Episode 45
Author Information
Regarded as a luminary at the intersection of technology and business transformation, Steven Dickens is the Vice President and Practice Leader for Hybrid Cloud, Infrastructure, and Operations at The Futurum Group. With a distinguished track record as a Forbes contributor and a ranking among the Top 10 Analysts by ARInsights, Steven's unique vantage point enables him to chart the nexus between emergent technologies and disruptive innovation, offering unparalleled insights for global enterprises.
Steven's expertise spans a broad spectrum of technologies that drive modern enterprises. Notable among these are open source, hybrid cloud, mission-critical infrastructure, cryptocurrencies, blockchain, and FinTech innovation. His work is foundational in aligning the strategic imperatives of C-suite executives with the practical needs of end users and technology practitioners, serving as a catalyst for optimizing the return on technology investments.
Over the years, Steven has been an integral part of industry behemoths including Broadcom, Hewlett Packard Enterprise (HPE), and IBM. His exceptional ability to pioneer multi-hundred-million-dollar products and to lead global sales teams with revenues in the same echelon has consistently demonstrated his capability for high-impact leadership.
Steven serves as a thought leader in various technology consortiums. He was a founding board member and former Chairperson of the Open Mainframe Project, under the aegis of the Linux Foundation. His role as a Board Advisor continues to shape the advocacy for open source implementations of mainframe technologies.
