Blog
IBC 2017: Optimizing Workflow and Content Delivery
Published on September 1, 2017Media workflows in broadcast, post-production and content delivery are continually challenged by ever-changing formats and camera resolutions, as well as emerging technologies…
WHPC at ISC: Diversity Can Refresh Perspective
Published on July 19, 2017Like many of you, I look forward to ISC each year for the opportunity to engage directly with customers, to catch up with colleagues…
Feature Preview: Improving Read Performance with L2RC Persistent Read Cache
Published on July 5, 2017Lustre* has emerged as a leading parallel file system that supports high-performance workflows and applications. Lustre has been designed with one assumption…
Bio-IT World 2017: Exploring Latest Groundbreaking Approaches in Life Sciences
Published on May 31, 2017This year marked the 15th anniversary of the Bio-IT World Expo in Boston, and storage was yet again a hot topic as life sciences organizations continue…
Big Data Challenges in Genomics
Published on May 22, 2017As we forge ahead to the $100 genome, the big data challenges in genomics continue to flourish. The complexity of genomic data is only increasing as we continue to sequence individual cells and organisms, creating profound challenges for managing and storing the data.
Lustre for Enterprise Computing: DDN’s Commitment and Increased Investments in Lustre, File Systems, and the Future of HPC
Published on May 1, 2017During the past decade, parallel file systems have redefined how we think about I/O performance. The largest parallel file system storage environments today deliver TB/sec of bandwidth while, at the same time, sustaining hundreds of thousands of metadata operations …
Accelerating the Genome Sequencing Process
Published on April 13, 2017DDN is changing how life science data is stored, shared, and analyzed. Our genomics research customers have documented massive throughput increases for their analysis pipelines with our simple, cost-effective way of scaling capacity and performance as data sets grow …