Adam Marko

Adam Marko


Recent posts by Adam Marko

1 min read

Supercomputing 2019: Storage Growth in HPC | Igneous

By Adam Marko on November 13, 2019

The International Conference for High Performance Computing, Networking, Storage, and Analysis (usually referred to as “Supercomputing”) is one of the largest and most influential technology conferences in the world. I’ve been attending since 2004 (I have the swag to prove it), and the changes since then are staggering. Infrastructure continues to evolve at a breakneck pace to meet the needs of a data driven economy, and the storage component is no exception.

3 min read

Why Data Visibility Matters to the Life Sciences

By Adam Marko on July 18, 2019

Last Friday, we talked about DataDiscover, and went over a few positive outcomes that our customers have achieved as a result of being able to make more fact-based decisions about their data. For our customers in the Life Sciences space, the presence or absence of data visibility is especially impactful to their success. Their concerns include everything mentioned in that article, but since the life sciences generates such massive volumes of data per employee (ie, per researcher), these customers have some additional concerns.

4 min read

Navigating the Unstructured Data Management Challenges of Next Generation Sequencing Workflows

By Adam Marko on May 1, 2019

Life science organizations face many challenges when it comes to the informatics component of their research. Scientific instrumentation is generating unstructured data at an unprecedented rate, and existing first tier storage systems can quickly reach capacity.

Next Generation Sequencing (NGS) is currently the largest consumer of storage capacity in the life sciences, but adding to expensive high performance storage as demands increase is not a sustainable or cost effective solution. Let’s look at the unstructured data management challenges of NGS workflows and possible solutions.

Topics: Life Sciences
2 min read

Accelerating Image Analysis and Cancer Diagnosis with AIRI from Pure Storage and Igneous

By Adam Marko on November 28, 2018

Artificial Intelligence (AI) has various applications today, from self-driving vehicles to optimizing workflows in manufacturing operations to detecting malware on the internet. Deep learning is a form of AI where multi-layer neural networks are utilized to transform input data into progressively more defined and useful outputs. Deep learning differs from machine learning (ML) in that ML focuses on the development of task-specific algorithms that can be applied to specific problems, while deep learning focuses on extracting information at multiple levels.

Topics: Igneous Solutions Life Sciences

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