How’s this for one big high-performance supercomputer: The IBM Blue Gene/P Intrepid at the Argonne Leadership Computing Facility (ALCF), located at the U.S. Department of Energy’s (DOE) Argonne National Laboratory, will soon earn the distinct honor not only as being the fastest computer in the world for open science, but also to be among the few to boost heavy-duty data analytics and visualization capabilities.
Argonne just awarded GraphStream Inc. a contract to make data analytics and visualization at this scale possible via the world’s largest installation of NVIDIA Quadro Plex S4 external GPUs. This new supercomputer installation, nicknamed Eureka and comprised of 104 dual quad core servers equipped with 208 Quadro FX5600 GPUs in the S4s, will allow researchers to explore and visualize the data they produce with Intrepid.
In just over a minute, Intrepid can produce the equivalent of 1,000 DVDs of data; the additional analytics and visualization capabilities will help scientists plow through this massive pool of data faster than before allowing them to uncover new insights, according to officials.
GraphStream, a supplier of scalable computer systems, will use the NVIDIA Quadro Plex (S4) visual computing system as the base graphics building block. Four high-end graphics cards will be placed in 1U “pizza box,” and this cost-effective configuration handles all the power and cooling issues associated with the graphics cards.
Robots that walk have come a long way from simple barebones walking machines or pairs of legs without an upper body and head. Much of the research these days focuses on making more humanoid robots. But they are not all created equal.
The IEEE Computer Society has named the top 10 trends for 2014. You can expect the convergence of cloud computing and mobile devices, advances in health care data and devices, as well as privacy issues in social media to make the headlines. And 3D printing came out of nowhere to make a big splash.
For industrial control applications, or even a simple assembly line, that machine can go almost 24/7 without a break. But what happens when the task is a little more complex? That’s where the “smart” machine would come in. The smart machine is one that has some simple (or complex in some cases) processing capability to be able to adapt to changing conditions. Such machines are suited for a host of applications, including automotive, aerospace, defense, medical, computers and electronics, telecommunications, consumer goods, and so on. This discussion will examine what’s possible with smart machines, and what tradeoffs need to be made to implement such a solution.