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Video of the Week - NoHardware.com destroys server huggers' equipment

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Back to Basics - How hardware virtualization works: Part 3

BY GREG PFISTER Since retiring from his position as an IBM Distinguished Engineer, Greg Pfister has worked as an independent consultant as well as serving as research faculty at Colorado State University. Pfister is the author of “In Search of Clusters,” and over his 30-year career, he has accrued over 30 patents in parallel computing and computer communications.

It is possible to find many explanations of hardware virtualization on the Internet and, of course, in computer science courses. Nonetheless, there remains a great deal of confusion regarding this increasingly popular technology.
This multi-part series attempts to provide an approachable explanation of hardware virtualization. You can see Part 1 here and Part 2 here.
Translate, Trap and Map The basic trap and map technique described previously depends crucially on a hardware feature: the hardware must be able to trap on every instruction that could a

Back to Basics - How hardware virtualization works
Part 1: Virtualization and cloud computing

BY GREG PFISTER Since retiring from his position as an IBM Distinguished Engineer, Greg Pfister has worked as an independent consultant as well as serving as research faculty at Colorado State University. Pfister is the author of “In Search of Clusters,” and over his 30-year career, he has accrued over 30 patents in parallel computing and computer communications.

It is possible to find many explanations of hardware virtualization on the Internet and, of course, in computer science courses. Nonetheless, there remains a great deal of confusion regarding this increasingly popular technology.
This multi-part series attempts to provide an approachable explanation of hardware virtualization. But before explaining hardware virtualization, we will have to put it in the context of cloud computing and other forms of virtualization.

Virtualization is not a mathematical prerequisite for c

Feature - Wireless grids: Squeezing a grid onto a widget

This diagram shows the layers from which WiGiT is composed.
Image courtesy WiGiT.

As wireless devices become increasingly common, and common devices become increasingly “smart,” wireless grids become increasingly practical. That means that the timing is perfect for WiGiT, a wireless grid testbed which will begin testing its alpha software in June.
The purpose of WiGiT (Wireless Grids innovation Testbed), according to the Syracuse University project leader Lee McKnight, is to refine open specifications for a wireless grid standard, and create a stable platform for experimentation.
“With WiGiT we expect to be able to do these large scale experiments from campus to campus, and we can run little experiments on that,” McKnight said. “Open specifications will make it easier for others to latch on.”
WiGiT, a National Science Foundation-Partners for Innovation program-funded collaboration between

Feature - Technology roundup: Science gateways and portals may level the playing field

Baseball diamond in a small town at night. Image courtesy Joe Y Jiang, Creative Commons

Our guest writer is Elizabeth Leake of TeraGrid — the high-performance, distributed computing network in the US. At the recent EGEE User Forum in Sweden, attendees had a chance to learn about two general-purpose portal engines and two domain-oriented portals. What these technologies have in common is the ability to act as “science gateways,” ultimately allowing new communities of researchers better access to advanced computing, thus leveling the playing field — a key part of “eScience.” Here is a round-up of some of the features pf these gateways, and who is developing them:VCR
Milan Prica from Sincrotrone Trieste, an independent laboratory in Italy, presented an advanced web portal with virtual collaboration features. The latest version of Virtual Control Room (VCR) inc

Feature - Scientific software goes parallel

Most scientists do their data analysis using commercial software over which they have little control. Yet, to take advantage of the multi-core processors new computers ship with, algorithms must be designed to run in parallel.
Luckily, many of the more popular scientific software packages have gone parallel. Some even offer versions or toolboxes that manage clusters or grids. iSGTW scoured the world of scientific software for the latest information on parallelization in scientific software.

Researchers at Cornell University used Windows HPC Server 2008 in conjunction with MATLAB to investigate turbulent combustion systems. Image courtesy Microsoft.

Excel
“More than 50 percent of customers cite lack of skills and complexity of integrated cluster solutions as inhibiting to adoption,” said Kyril Faenov, general manager of Microsoft’s technical computing group. “On the other hand, we know that more than 50 pe

Virtualization - putting all the spinning plates on one stick

Image courtesy Don Fulano, Flickr

To give a better idea of what virtualization is and how it can be used, we look at recent developments at CERN, using it as a sort of case study.
In the words of EGEE director Bob Jones, a computer center operates “a lot like the guy spinning plates at the circus. He’s got more and more plates spinning on more and more sticks, and he’s running around trying to keep them all going.”
At the typical computer center, one machine is doing graphics, one is doing electronic document handling, and one is doing something else.
“But what virtualization does it put all those plates on one stick,” said Jones. “You don’t need several different physical machines, but have everything running on one machine doing everything.”
As a result, it’s faster and more efficient.
Virtualization technology is not a new idea. Virtual memory was develope

OSCAR understands the language of chemistry, naturally

When it comes to chemistry terminology, one person’s sodium chloride is another’s salt. Image courtesy Snack/stock.exchng

Like any other language, the language of chemistry lacks uniformity.
New words are invented, old words fade out of use, styles of writing change and some writers suffer from less-than-perfect grammar.
What’s more, there is no single way of referring to a chemical: one person’s salt is another’s sodium chloride (and yet another’s NaCl). To search for a specific word in a chemistry text, a researcher must take into account every permutation of that word and every possible mistake in representing it.
This is highly inefficient, and with more sources of chemistry information becoming available every day, it’s not getting any easier to find relevant information.
But now, there’s OSCAR to help. Also known as “Open Source Chemistry Analysis Routines,” it

Video of the week - Computation and tomography

Watch the video of the week, and then read on to learn more about tomography and computation.

This video originally appeared in SLAC Today. Video courtesy of SLAC.

To get the most use out of tomographic images, they need to be assembled into a three-dimensional image. This is accomplished using a computational process called tomographic reconstruction. The amount of processing power necessary to create these visualizations varies widely, depending on a variety of factors, such as resolution and size.
“Our tomography computations are handled first order by the software provided by the company that made the microscope, Xradia Inc,” said Joyce Hayter, the researcher who appears in the video. “We also do further visualization using the commercial software Avizo, and our postdocs also write in-house code with MATLAB.”

Back to Basics - Why go parallel?

BY DARIN OHASHI Darin Ohashi is a senior kernel developer at Maplesoft. His background is in mathematics and computer science, with a focus on algorithm and data structure design and analysis. For the last few years he has been focused on developing tools to enable parallel programming in Maple, a well-known scientific software package.

Parallel programs are no longer limited to the realm of high-end computing. In this column, Darin Ohashi takes us back to basics to explain why we all need to go parallel.
Computers with multiple processors have been around for a long time, and people have been studying parallel programming techniques for just as long. However, only in the last few years have multi-core processors and parallel programming become truly mainstream. What changed?
For years, processor designers have been able to increase the performance of processors by increasing their clock speeds. But a few years ago, they ran into a few serious problems. RA

Feature - Lining up new grid users with gqsub

Stuart Purdie, of the University of Glasgow, receives an award for his work on gqsub, from Bob Jones of EGEE. Image courtesy EGEE09

Grid computing is often seen as the domain of big science, involving giant experiments and massive number crunching. What if you’re not working on these huge scales? What if your work is too big for a local cluster but “too small for the grid?”
Welcome to ‘mesoscale’ computing, that middle ground between the applications that use 10 minutes on your desktop and 100 hours on the grid.
Researchers who fall into this area are usually well looked after by local resources. However, for various reasons — maybe a high demand from other users, or just investigating something unusual — a user may want to move on to the grid. This move can be tricky when the user is faced with another interface they have to learn or a completely different way of getting their work done.

Word of the week - Transparent

Image courtesy of ilco at stock.xchng.

All too often, common words take on new and unexpected meanings within a scientific or technical discipline. And to the uninitiated, this can be incredibly confusing.
The word ‘transparent’ is a great example of such a word. The most basic definition for transparent is ‘see-through.’ In other words, allowing light and information to pass through.
When journalists say that we should strive to be transparent, we mean that we should strive to provide readers with details on how we got our information and reached our conclusions.
In the computing world, however, the word takes on an entirely different meaning. In fact, you could say it takes on the opposite meaning.
When a developer says that a science gateway should be transparent, that means that the scientists who use the gateway should not need to know anything about how it works. Any black box system would be considered likewise ‘tran