IT/Datacenter & Super Computing News - Page 23
Microsoft has announced a victory in the MinuteSort test. They claim to have tripled the amount of data sorted by the previous record holder, a Yahoo team. MinuteSort is a test to see how much data can be sorted in just a mere 60 seconds. As more data moves into the cloud, this ability to sort data quickly becomes a bigger and bigger issue.
According to Microsoft's post on TechNet, "In raw numbers, the team's system sorted 1401 gigabytes in just 60 seconds - using 1033 disks across 250 machines." This hardware compared to what Yahoo ran is roughly "one-sixth of the hardware resources" and managed to sort around 3 times as much data. You can see that the Microsoft solution is much more efficient.
Additionally, it's interesting to note that Microsoft Research didn't use Hadoop as one might expect. Instead, the researchers at Microsoft created a new system called "Flat Datacenter Storage." The "flat" portion is the important part of the system. Microsoft explains:
[Microsoft Research's Jeremy] Elson compares FDS to an organizational chart. In a hierarchical company, employees report to a superior, then to another superior, and so on. In a "flat" organization, they basically report to everyone, and vice versa.
Google and green, it goes hand-in-hand and their next data center will be built with energy savings in mind. Google have previously been good at this with other data centers that are energy-efficient and green. Their latest data center to be built in Taiwan will use thermal energy storage.
Thermal energy storage systems commonly use chilled liquid or ice to act as a thermal battery, enabling a data center operator to run air conditioning at night (when rates are obviously cheaper) and during the day, pump the chilled liquid around the facility for cooling.
Increasing electricity rates in Taiwan will be a big reason for Google to tap the thermal storage solution, where they can skip the peak power rates at night and just use liquid or ice as its also cleaner, and a longer lasting way to store energy rather than using batteries. A Google exec has cited the the increasing electricity rates in Taiwan is a reason for building the new system, and also notes that the new Taiwan-based data center will use 50-percent less energy than typical facilities.
Google is planning on spending $700 million on three new data centers in Taiwan, which will be the the company's third data center cluster in Asia, after their first two stops for construction in Hong Kong and Singapore. This will be the first time that Google have used thermal energy storage systems for a data center.
IBM over the next five years will build a low-power, exascale computer for largest-ever radio telescope, promises it won't be Skynet
Over the next five years, IBM is set to work with the Netherland's National Institute of Radio Astronomy (ASTRON) where tehy hope to develop a low-powered, exascale supercomputer. Not impressed yet? Hold onto your chair, dear reader. According to IBM, this supercomputer would be millions of times faster than today's high-end desktop PCs, and possibly thousands of times faster than even the most recent super computers.
The exascale computer would be used to analyze data collected by SKA (square-kilometer array), which is a cutting-edge radio telescope set to become the largest and most sensitive of its kind ever built. ASTRON hopes to have the telescope ready by 2024. While it's still a fair way off, the excitement will only build over time.
Now, this is where you don your math hat, and get ready to have your eyes widen a little: to compare to what we know, and use now, exascale refers to a computing device that is just incredibly fast, where the number of floating-point operations per second it can perform isn't measured by gigaflops or even petaflops, but exaflops. Today's highest-end desktop CPUs rank up around 20 gigaflops, not that impressive in terms of scale to this beast.
Well not really. Or rather, not yet.
Columbia doctors want to use Watson to diagnose patients, so they've been testing "him" for almost a year to see how the trivia super computer stacks up in medical problem-solving.
The project is led by Herbert Chase, a professor of clinical medicine in the Department of Biomedical Informatics. Through a series of tests, questions, inquiries, and experiments, Chase hopes to retrofit the knowledge bot with an understanding of diagnostic medicine.
Chase said in the Columbia news release.
"It's been impossible for probably 20 or 30 years for a human to process the information required to practice medicine at the highest, evidence-based, guideline-based level,"
Evidently, the minute "trouble" that Watson had with some of the JEOPARDY! questions is a bonus for the researchers. During the popular game show, contestants got a live feed of Watson's logic processing in reference to the posed question (answer?). There were often two or three wrong answers with probability factors accompanying each possibility. The stakes are a much higher in medicine, as well as the vast amount of information available. Try entering in "headache" as a symptom in any web-based diagnosis site and you'll get hits on everything from Hangover to Brain Tumor.