Software-defined computing

Evolving high-performance computing to deal with mountains of data

Share this post:

Whether it’s the universe, the Earth’s population, your waistline, or data and compute capacity, coping with expansion is high on everyone’s agenda.

Data volumes are expanding in leaps and bounds, while at the same time compute capabilities are being greatly enhanced with technologies like hardware accelerators. Technologies have advanced to store and process massive amounts of data, resulting in new generations of very high-resolution models, and this delivers better-quality products to market faster than ever before. However, this is not without its challenges. Managing and moving large data volumes has become a major pain point in computing.

To address data management challenges, organizations with high-performance computing (HPC) environments are looking at how to minimize data movement and how to run their workloads where the data already resides. These are complex questions, especially when we move to multiple compute clusters scattered across the globe, all while competition and pressure to cut costs mounts.

Expanding from traditional compute-centric HPC to a data-centric model is a natural way to meet these challenges. Here are five key considerations for a data-centric approach to high-performance computing:

  • Orchestration of storage and compute resources; moving and caching data when it makes sense
  • Tailoring resources to workloads; considering workload types when selecting storage medium, processors
  • Storage intelligence; directing applications to the closest data
  • Storage efficiency; how to bring in data more quickly, speed operations on data
  • Data management, including long term storage

Learn more about these five key considerations for implementing a data-centric HPC approach in the white paper here. Get faster results and lower your investment with data-centric HPC solutions for storage and compute—all while creating a more flexible, data-centric HPC infrastructure.

As for the waistline reduction strategy, we’ll leave that up to you and your New Years resolutions!

More stories

Think 2020: How to update and refocus your skills

Big data & analytics, Modern data platforms, Workload & resource optimization

If you had to choose just one major IT conference to attend this year, then what’s the best option for exploring a mix of future possibilities and today’s practical use cases? Imagine an event where you can acquire forward-looking insights and practical hands-on experience, together. Do you want to meet industry experts who are already more

The Hybrid IT independence proclamation

Hybrid cloud, Modern data platforms, Workload & resource optimization

It’s a new year and decade — full of plans for digital business transformation. The progressive leader’s expectation from IT investment has evolved. “Better, faster, cheaper IT” isn’t compelling enough to satisfy the rising demand for new technology deployments. Anticipated business outcomes from IT transformation is the top priority. IT platform comparisons are very relevant more

Practices, tools and expertise for better storage performance

IBM Systems Lab Services, Storage, System software

Houston, we have a problem. Call the storage experts, now! When their customers complain about long wait times for online payments, lagging video streams and other impacted services, businesses tend to quickly and without prior analysis blame their storage appliances. While your data resides primarily in storage systems, that doesn’t necessarily mean that your storage more