Edison2 is still hard at work designing the next generation of its Very Light Car (VLC).
We’ve written about the development of the next-gen VLC before. Edison2 has also expanded its design team (including engineers who previously worked with Mercedes and Northrop Grumman), and is developing an electric version of the car. Altair ProductDesign recently announced it had been tapped to conduct a three-phase engineering study looking at suspension sensitivity, vehicle impact strategy, and structural optimization for the VLC 4.0.
I have a full plate of meetings at Supercomputing 2011 this year. Below are some of the points of interest I am learning about along the way that I wanted to share.
Yesterday I attended the 7:30 breakfast meeting for Platform Computing’s MapReduce. This is a policy-driven workload manager and scheduler that handles mixed types of workloads running on the same cluster. It uses an open architecture to support multiple applications for jobs built with Hadoop MapReduce technology. Applications include Pig, Hive, Java, Oozie, Cumbo, and natively written Java MapReduce programs.
The scheduler can give the high-performance computing (HPC) manager options to schedule job submissions with a Fairshare Scheduler, Preemptive Scheduler, Threshold-based Scheduler or Task Scheduler. It also helps to work with resource draining.
MapReduce sends the application to a Job Controller, which decides what data should be mapped to an input folder and what mapped tasks should go to the local storage. It can split data so only that data that needs to be in the compute schedule goes to the CPU. It also uses Resource Groups to move data between local workstations.
Platform Computing’s MapReduce can allow clusters to be grouped into one large resource. Platform is used as a massive scheduler. The user has control of the job not just when it is in the queue, but while the job is running. Continue reading