Taking a Look at Emerging Technologies
Scientific Computing is excited to be celebrating its 30th year in 2014, and we have a terrific line-up of new things we will be introducing throughout the coming months. This includes our first combined issue of Scientific Computing and HPC Source, and a new global cross-platform app that is available across multiple devices and allows you to browse and read each issue anytime, anywhere.
In our latest issue, we explore the theme of “Emerging Technologies.” Our cover story takes a close look at how big data and HPC are coming together to address the major opportunities and challenges of the 21st century. And our expert contributors share points-of-view on topics ranging from the latest big data tools, to mobile-to-HPC applications, to fostering bi-directional data flow.
In “Create Mobile to HPC Applications using a Single Source Tree,” Rob Farber, an independent HPC expert, talks about how basic tools are now available to test efficacy and explains why he feels it’s worth taking a look. While William Weaver, an associate professor in the Department of Integrated Science, Business and Technology at La Salle University, looks at how big data tools, such as Grok and IBM Watson, are enabling large organizations to behave more like agile startups in “Need for Speed: Ramping up the Velocity of Big Data.”
Mobile informatics has tremendous potential to improve productivity, and Seamus Mac Conaonaigh, Director of Technology, Informatics at Thermo Fisher Scientific, provides his perspective on “The Smart Lab: Fostering Bi-directional Data Flow.” Also, in “Informatics Snapshot: METTLER TOLEDO LabX,” John Joyce, a laboratory informatics specialist based in Richmond, VA, explains why — when it comes to control and integration with laboratory instruments — this application excels. And John Wass, a statistician based in Chicago, IL, looks at “a very efficient and extraordinarily useful tool for chemical and biological projects” in “SciFinder: Chemistry/Biology References and More.”
Size alone does not define big data — it is best defined as a combination of volume, velocity, variety and value —and Mark Anawis, a Principal Scientist and ASQ Six Sigma Black Belt at Abbott, provides an update on how “Big Data Analytics Continues to Evolve.”
As always, we invite you to pass this information along to colleagues who also may find its contents valuable, and we welcome your suggestions for future issues.