Big data is exploding. With incredibly powerful and dynamic business intelligence (or BI) tools being developed daily and incredibly complex data warehouses, data mart schemas, and data lakes being constructed in the cloud, data has never been more valuable. But what about… [...]
Read MoreHigh throughput and next-generation sequencing (NGS) have significantly increased the quantity of raw and processed genome sequencing data researchers need to manage. To compound matters, sequencing data is routinely stored in redundant sets as researchers process and annotate data iteratively and seldom,… [...]
Read MoreBig data, defined as a massive volume of structured and unstructured data that is difficult to process via traditional technology, holds a wealth of possibility; but, standard, traditional parallel relational database technology has not proven to be cost-effective or provide the high-performance… [...]
Read MoreBefore we delve into issues pertaining to Machine Learning (ML) and storage optimization, it’s crucial for the reader to understand what ML is and how it works. A subset of Artificial Intelligence (AI), ML is a technique centered around training algorithms to… [...]
Read MoreA parallel file system enables systems simultaneous, coordinated access to data across multiple storage servers over a high-performance network such as OmniPath or Infiniband. High-performance computing (HPC) parallel applications require parallel file systems to take advantage of multiple IO paths and distributed… [...]
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