Overcoming the Storage Roadblock with OceanStor Pacific

It’s no secret that High-Performance Computing (HPC) is playing a critical role in the world’s technological development. Not only has it become a foundation for digital transformation but also a key driving force for social, scientific, and economic progress. In fact, HPC underlies almost any great scientific feat or industrial innovation of our time – from pharmaceutical and automotive R&D, to genome sequencing, it helps us tackle some of the world’s most complex challenges with unmatched speed and efficiency. 

In recent years, huge advances in HPC have helped lower its technical requirements and make it both more accessible and less costly. Thus, it’s hardly surprising that more and more companies are turning to HPC to fuel service innovation and decision-making. However, despite its progress, HPC still faces a major challenge that we must overcome in order to truly unleash the power of data: the storage roadblock.

Confronting the Storage Roadblock

Exponential data growth has caused HPC to become closely integrated with big data and evolve from computing- to data-intensive. Now, for organizations to truly tap into the potential value of data, they require frequent access to it. This is where High Performance Data Analysis (HPDA) comes in.

Recognized as the confluence of big data and HPC, HPDA gives enterprises the ability to interrogate and analyze huge data sets in real time, opening unprecedented opportunity. IDC data suggests that 67% of HPC resources are now used for HPDA, with machine/deep learning and fraud detection applications the most commonly used. This leads us to believe that emerging HPC scenarios such as HPDA will be the next milestone in HPC development.

Before we can fully enjoy the benefits of HPDA, however, we must first address the storage roadblock. It’s a well-known fact that, in the process of computer development, CPU performance increases much faster than that of storage and I/O. Indeed, a data center performance survey conducted in 2014 showed that the CPU performance increased by 52%, while the memory and the I/O performance increased by 6% and 9%, respectively. Yet, it was the storage performance that saw the lowest improvement. This was not only related to the physical performance of the media but also to the storage protocol, both of which were exceptionally slow.

So, why does this matter? If the storage performance is lower than the CPU and memory bandwidth performance, the data access capability will be lower than the data processing capability, which hinders an organization’s ability to deliver real-time services, reduces efficiency, and wastes data center resources.

The speed gap between computing, storage, and I/O becomes increasingly significant as computers evolve. However, the explosion of applications in emerging HPDA and HPC-based AI scenarios has given way to an urgent need for real-time high-performance big data analytics, making it urgent we overcome the storage roadblock.

Pushing the Boundaries of Possibility

However, where there are challenges, there are opportunities. To balance the growth of computing and storage performance and power the HPC industry upgrade to HPDA, Huawei has developed the next-generation storage for HPDA: the OceanStor Pacific.

In the past, insufficient storage capacity caused nodes to pile up, which consumed power and ate into IT budgets. With its ultra-high density design, Huawei OceanStor Pacific confronts this problem by increasing the capacity and performance densities per unit space to minimize the footprint and TCO. Put simply, it gives you more, for less.

At the same time, the OceanStor Pacific is designed for hybrid workloads. One storage system supports both high bandwidth and IOPS, while each rack unit (U) provides 32 Gbps bandwidth and 400,000 IOPS, ensuring higher performance in all scenarios. Take oil and gas exploration as an example. Seismic data processing requires high bandwidth, while seismic data interpretation needs high IOPS. In this case, one OceanStor Pacific device can achieve both goals, breaking the storage roadblock and making performance problems a thing of the past.

That’s not all – in emerging HPDA scenarios such as autonomous driving, precision medicine, and intelligent manufacturing, the file, object, and HDFS services may be used in different phases of a pipeline. Traditionally, the three services are provided separately by three storage devices, meaning data must be copied multiple times between devices, impacting efficiency and wasting storage space. To tackle this, Huawei OceanStor Pacific supports lossless interworking of multiple protocols, including NFS, SMB, HDFS, and S3. This allows one data copy to be shared with multiple services. It’s smarter to keep things simple.

Unlocking the Potential of Data for Something Big

Effective data utilization requires high-performance storage and computing capabilities. Without this, data is simply clutter in the virtual world. That’s exactly why Huawei launched the OceanStor Pacific next-generation storage for HPDA; through the integration of cutting-edge technologies, it eliminates the gap between computing and storage performance and breaks the storage roadblock.

As a result, the OceanStor Pacific has been widely adopted in HPC scenarios across various industries. Whether it’s powering groundbreaking scientific research, improving meteorological data analysis efficiency, or enhancing oil and gas data processing, Huawei OceanStor Pacific is helping organizations overcome the storage roadblock to turn data into discoveries and fully embrace digital transformation.

Find out more about the Huawei OceanStor Pacific Series.

Further Reading:

Huawei OceanStor Pacific series storage wins Best of Show Award Grand Prize in the Server & Storage Division at Japan’s largest ICT exhibition, Interop Tokyo 2021.

Disclaimer: Any views and/or opinions expressed in this post by individual authors or contributors are their personal views and/or opinions and do not necessarily reflect the views and/or opinions of Huawei Technologies.