Summary
Traditional storage has become a bottleneck, limiting the full potential of HPC environments. The future of HPC and scientific breakthroughs hinges on having a platform that is specifically engineered for these data-intensive workloads.
High-performance computing (HPC) sits at the intersection of scientific discovery and technological innovation—whether it’s simulating climate models, analyzing genomic data, or training massive AI models. The computational demands of its workloads are growing exponentially, causing traditional storage approaches to become critical bottlenecks, limiting the full potential of HPC environments.
It’s why the most successful HPC deployments will have one critical thing in common: a massively scalable storage platform capable of feeding these powerful systems.
The Data Challenge: Why Traditional Storage Can’t Keep Up
High-performance computing environments generate and process enormous volumes of data at unprecedented speeds. The evolution of GPU technology and specialized accelerators has created computational capabilities that can process data faster than conventional storage systems can provide it. This imbalance creates a fundamental problem: even the most powerful computing systems can only work as fast as they can access their data.
Traditional storage solutions, originally designed for predictable workloads, often struggle with several critical aspects of modern HPC requirements:
- Massive concurrency: HPC workloads frequently involve thousands of parallel processes requiring simultaneous access to data.
- Metadata performance: Beyond raw throughput, the ability to handle billions of metadata operations becomes critical.
- Scalability: As data sets grow to petabyte- and exabyte-scale, storage systems must scale both capacity and performance linearly.
- Energy efficiency: The computational density of modern HPC clusters demands storage solutions that minimize power consumption and cooling requirements.
According to recent findings from Intersect360 Research, these bottlenecks represent some of the most pressing issues facing the HPC-AI industry today. Organizations increasingly find their expensive GPU resources sitting idle, waiting for data to process.
The Pure Storage Approach to HPC Storage
At Pure Storage, we’ve reimagined storage architecture from the ground up to address these fundamental HPC challenges. Rather than adapting legacy designs, we’ve built a platform specifically engineered for modern data-intensive workloads.
Our approach centers on three core principles:
- Massively parallel architecture: Like HPC itself, storage must operate in a highly parallel fashion to achieve maximum throughput.
- Flash-native design: DirectFlash® technology enables us to manage flash NAND natively rather than mimicking hard disk behavior, dramatically improving performance, reliability, and efficiency.
- Simplified management: HPC environments are complex enough without adding storage management overhead.
This philosophy has culminated in our latest innovation designed specifically for the most demanding HPC and AI workloads.
Introducing FlashBlade//EXA: Redefining Performance at Scale
We’re proud to introduce FlashBlade//EXA™, the industry’s most powerful data storage platform built to power AI factories and HPC environments by delivering extreme throughput at unprecedented scale. This groundbreaking solution addresses the fundamental challenges that have constrained HPC storage until now.
FlashBlade//EXA represents a paradigm shift in storage architecture with several revolutionary capabilities:
- Unprecedented performance: The platform delivers over 10TB/s read speed and write performance, as high as 50% of read at general availability this summer.
- Disaggregated architecture: Independent scaling of data and metadata planes eliminates traditional bottlenecks.
- Massively distributed metadata: Our proven metadata core can support billions of operations and over 20 times the file systems in a single namespace compared to alternatives.
- Industry-standard integration: Leveraging common protocols and off-the-shelf hardware for the data plane ensures seamless integration into existing environments.
As Rob Lee, Chief Technology Officer at Pure Storage, explains: “FlashBlade//EXA delivers a massively parallel architecture that enables independent scaling of data and metadata to provide customers with unmatched performance, scalability, and adaptability for some of the largest, most demanding data environments in the world. Storage is now accelerating the pace of large-scale HPC and AI evolution.”
Real-world Impact: Pure Storage and CERN Partnership
The true test of any technology is its real-world application. That’s why we’re particularly excited about our recently announced partnership with CERN openlab, the European Laboratory for Particle Physics, to accelerate the development of cutting-edge ICT solutions for the Large Hadron Collider.
CERN generates massive volumes of data through its high-energy physics experiments, data that must be effectively recorded, stored, and analyzed to advance our understanding of the universe. Traditional storage solutions have become significant bottlenecks for their high-performance computing needs.
Through this multi-year agreement, Pure Storage and CERN openlab will:
- Explore how DirectFlash technology can support the needs of future scientific research
- Optimize exabyte-scale flash infrastructure for Grid Computing and HPC workloads
- Identify opportunities to maximize performance in both software and hardware while improving energy efficiency
“Together with CERN openlab, we are pushing the boundaries of what’s possible in HPC and Grid Computing environments supporting cutting-edge scientific workflows,” said Lee. “With the integration of our state-of-the-art technology in CERN’s large-scale distributed storage system, CERN openlab is ready to tackle the unprecedented volumes of data with unparalleled speed and reliability while empowering researchers for the extraordinary challenges posed by the High-Luminosity Large Hadron Collider (HL-LHC) era.”
Luca Mascetti, Storage CTO at CERN openlab, adds: “We expect this partnership will deliver some key wins as we look to the future of storing scientific experiments data. First, we expect to integrate this technology into our large-scale distributed storage system and to deliver data more effectively, providing a way to scale storage performance beyond what is possible today. Second, we are hoping to unlock the next generation of high-energy physics breakthroughs at CERN and demonstrate to the broader scientific community the potential for enhancing storage capabilities, ultimately accelerating the pace of discovery and innovation at research institutions globally.”
The Bigger Picture: Addressing Industry-wide HPC Challenges
Beyond raw performance, our approach addresses several critical challenges facing the HPC industry in 2025:
Supply Chain Resilience
The global HPC landscape continues to face significant supply chain challenges, with lead times for high-end GPU servers and components ranging from 6 to 12 months. By supporting off-the-shelf servers for the data plane, FlashBlade//EXA offers greater flexibility in infrastructure planning and deployment.
Energy Efficiency
As HPC deployments grow, power consumption and cooling requirements become increasingly problematic. The impressive performance density of 3.4TB/sec per rack of FlashBlade//EXA helps optimize the ever-growing power and cooling costs associated with energy-hungry GPU environments.
Simplified Management
The shortage of skilled personnel in computational sciences and HPC-AI system management represents a significant industry challenge. Our focus on simplified management reduces operational overhead, allowing organizations to deploy and manage high-performance storage without specialized expertise.
Accelerating Innovation across Industries
The impact of advanced storage technology extends beyond traditional HPC environments. We’ve seen remarkable results across diverse industries.
In genomics research, the University of Helsinki leveraged FlashBlade® to significantly accelerate its work on the Birch Genome Project. “It was important for us to do things in parallel, and moving to FlashBlade has enabled us to significantly speed up the process,” said project lead Assistant Professor Jarkko Salojarvi. With FlashBlade enabling them to run up to four jobs in parallel, the team crossed the project’s halfway mark in just 18 months, completing more than 550 genome assemblies compared to less than 100 in the same timeframe with sequential processing.
In large-scale AI, organizations like Meta have relied on FlashBlade to scale their AI workloads efficiently. As AI models grow in size and complexity, the storage infrastructure becomes increasingly critical to successful outcomes.
The Path Forward: Storage as a Catalyst for Discovery
As we stated earlier, even the most powerful computing systems can only work as fast as they can access their data. For HPC to live up to its name, storage technology will play an increasingly vital role. The traditional view of storage as a passive repository is giving way to a new understanding: storage as an active accelerator of computational workloads.
By removing data access bottlenecks, solutions like FlashBlade//EXA don’t just support HPC workloads—they fundamentally transform what’s possible. Researchers can work with larger data sets, run more complex simulations, and iterate more rapidly, ultimately accelerating the pace of discovery.
The Pure Storage vision for HPC storage combines unprecedented performance with radical simplicity. We believe that by eliminating storage bottlenecks and complexity, we can help unlock the next generation of scientific and technological breakthroughs.
In a world where computational power continues to grow exponentially, having storage infrastructure that can keep pace isn’t just an advantage—it’s a necessity. The future of HPC depends on it.
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