Panasas adds all-flash and massive-capacity data solutions to ActiveStor portfolio

Panasas has unveiled its new portfolio of high performance storage solutions for the industry’s most complex data challenges. Two new ActiveStor systems will accelerate advanced AI/ML training, modelling and simulation, high performance data analytics, and massive-scale data workloads.

  • 1 year ago Posted in

All-NVMe ActiveStor® Flash and massive-capacity ActiveStor® Ultra XL now join Panasas’ industry-leading price/performance storage platform, ActiveStor® Ultra. The new portfolio is powered by the company’s flagship PanFS® data engine, the original parallel file system for Linux clusters.

Mark Nossokoff, Research Director and Lead Storage Analyst at Hyperion research, remarked, "We've witnessed a significant 13% increase in on-premises HPC spending from 2020 to 2021 and are projecting a market growth CAGR of 6.4% over the 2026 forecast horizon. The growth is largely driven by organisations' emerging use cases, such as AI/ML and big data analytics, that require new technologies and solutions from the HPC space to address some of today’s biggest challenges. We’re excited to see an HPC storage veteran vendor like Panasas embrace these newer workloads with their new portfolio of ActiveStor storage appliances.”

 

Panasas’ PanFS data engine is the world’s leading parallel file system and the heart of the ActiveStor storage family. It is exceptionally simple to manage, yet it delivers extreme performance, unlimited scalability, and unparalleled reliability. The industry-pioneering PanFS software is a reliable and autonomic data management engine built on 20+ years of hardening through commercial deployment. This powerful data engine takes the complexity out of high performance data environments and provides high-speed direct file-based data access to applications with no manual administration required. It orchestrates all data management to automatically recover from failures, continuously and seamlessly balance data loads, and scrub and encrypt stored data for the highest levels of protection.

 

The introduction of the ActiveStor portfolio is validation of the PanFS data engine’s robustness, as well as Panasas’ ability to easily deploy tailored data solutions that meet customers’ specific workload, footprint, and environmental requirements.

 

“Forward-thinking organisations are harnessing the exponential data growth we’re seeing today to build a brighter tomorrow, from developing life-saving pharmaceuticals to designing energy-saving autonomous vehicles. The technology they use to store, deliver, and secure their data is vital to their success,” said Tom Shea, Panasas President and CEO. “Choosing the optimal data foundation for your organisation’s specific needs and goals is not just a good business strategy – it’s imperative. That’s why we’re introducing a portfolio of products for the first time in our history. Our storage systems have been purpose-built to provide a diverse range of high performance data solutions for all workload types at the best total cost of ownership.”

 

The ActiveStor products are optimally suited to a variety of computing environments across industries.

 

ActiveStor Flash. The new all-NVMe ActiveStor Flash provides outstanding scratch and small- and random-file storage performance. It is ideal for AI/ML training, trading strategy backtesting, as well as life sciences and electronic design automation projects.

ActiveStor Ultra XL. The new high-capacity ActiveStor Ultra is optimal for massive-scale data environments in addition to workloads with cooler and reference datasets and large file sizes, such as seismic resource exploration; scientific, academic, and government research; manufacturing; and media and entertainment.

ActiveStor Ultra. The hybrid ActiveStor Ultra has been a stalwart high performance mixed workload solution for traditional and enterprise HPC. It delivers exceptional performance for high performance data analytics, complex modeling and simulation, molecular imaging techniques in life sciences, and converged HPC/AI data use cases.

 

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