Big Data and HPC
Explore how high-performance computing is reshaping big data analytics in enterprises with cost-effective solutions like clusters and RAID arrays.
High-Performance Computing in the Enterprise: The Era of Big Data
From Science Labs to Business Floors
High-performance computing (HPC) has moved beyond its roots in scientific and engineering applications like weather modeling and nuclear simulations. With the rise of big data, enterprises are adopting HPC to process and analyze vast streams of information generated by online shopping, social media, customer interactions, and network events.
Two Strategies for Achieving HPC
- Supercomputers:
- Traditionally associated with HPC.
- Extremely powerful but prohibitively expensive for most enterprises.
- Clusters of Commodity Hardware:
- A cost-efficient alternative leveraging standard servers connected by high-speed networks.
- Enabled by solutions like Hadoop MapReduce, which distribute processing tasks across multiple machines.
The Role of Parallel File Systems
To meet the extreme input/output (I/O) demands of HPC, enterprises rely on parallel file systems such as:
- IBM General Parallel File System™ (GPFS™)
- Zettabyte File System (ZFS)
These systems allow CPUs to access large datasets simultaneously, speeding up data processing across clusters.
RAID Arrays as the Foundation
High-speed RAID solutions are essential for HPC deployments, offering:
- Robust support for parallel file systems.
- Affordable and efficient throughput for handling massive data transfers.
Why HPC Matters for Businesses
In today’s data-driven world, success depends on extracting actionable insights from big data. Companies equipped with practical and cost-effective HPC solutions will gain a competitive edge by processing information faster and more efficiently.
