Monthly Archives: September 2013

We all know that memory is a key part of data-intensive science. Besides the obvious reason that we need memory in order to store information/data. Memory has several other key features that are core parts of Data-intensive science. As explained … Continue reading →

A library in computational science is where digital data is stored for future use. Libraries generally consist of collections of files, databases, models, code, and etc. For instance, a library of code can contain lots of pre-written segments that can … Continue reading →

Why are bytes used as the primary way to measure information? How are 8 bits of memory able to describe information delivered to end users? A series of benchmarks are used to properly evaluate the total number of bytes delivered. … Continue reading →

Data centers are the back bone and the future for many companies, organizations, governments, and research groups.  From cloud computing to quick search queries, data centers are used in a number applications – one of the most important of which … Continue reading →

Originally posted on ilundy:
Smart recycle bin wins record-breaking MHacks hackathon      One of the cooler things about going to the University of Michigan is the immense amount of students that attend here and the opportunities that arise as…

Originally posted on ilundy:
      Data Centers are massive facilities that house computer systems that carry out extremely extensive computational problems. Data centers are essential for Data-Scientists. Much of the work Data-Scientists are involved with take years and…

Transferring large amounts of data is expensive, both in time and energy. As scientific research moves more and more into the real of large-scale information analysis, this becomes more important. Using cloud computational services allows data to be worked on … Continue reading →

Parallel computing is a fairly new term and has helped the world with many different situations and problems. As many of you probably already know, parallel computing is using more than one computer hooked up through a network, or one … Continue reading →