It’s that time of year again, MoabCon 2014! Join the Adaptive Computing team from March 31 to April 3 in Park City, Utah. The theme of the conference is “Accelerate Insights,” and will teach Moab users how to streamline the analysis process, reducing the time to discovery.
MoabCon 2014 brings together Adaptive Computing customers, partners and industry experts for four days of talks, technical sessions, and networking events. The conference features keynotes and sessions from Adaptive Computing’s management team as well as presentations from heavyweights within the industry.
Take a look at some of the MoabCon 2014 speakers:
- Partners – HP, Cray and others
- DigitalGlobe – Jason Bucholtz
- The Dow Chemical Company – Dave Powers
- National Institute for Computational Sciences, University of Tennessee – Troy Baer
- Sandia National Laboratories – Sue Kelly
- Lawrence Berkeley National Laboratory – Michael Jennings and Jay Botts
Adaptive Computing will also introduce new product enhancements, including its recently unveiled Big Workflow solution that processes intensive simulations and data analysis faster, more accurately and cost effectively.
“We are excited to gather with the industry’s foremost experts to explore the evolution of big data analytics, coupled with the collision of cloud and HPC, at this year’s Moabcon,” said Rob Clyde, CEO at Adaptive Computing. “MoabCon has always been a wonderful place to unplug and get creative.”
During the conference, Adaptive Computing will honor its customers with the second annual Adaptie Awards. Awards are given to organizations and individuals that continually push the technological envelope using Adaptive Computing’s software. Awards will be given to customers for Best Use of Moab in an HPC Environment, Best Use of Moab in a Big Workflow Environment, and Lifetime Achievement. Take a look at the 2013 Adaptie Award Winners.
Register for MoabCon 2014 and we’ll see you on March 31!
The post MoabCon 2014: Experts Gather to Discuss the Latest in HPC, Cloud Computing, and Big Data appeared first on Adaptive Computing.
