Author Archive

How can getting to the ocean help with HPC computing?

SMPs may have cores, but clusters have bandwidth.

Data locality is the key to efficient code.

Will multi-core split HPC into two programming camps? Which one will you join?

As multi-core solutions continue to grow, a new power saving single-core server approach takes hold

“Making the world’s knowledge computable” — Sounds like a job for parallel computing.

To the casual observer, cloud computing often looks like grid computing, but from an HPC perspective it is not even close.

As GPU Clusters hit the market, users are finding small code changes can result in big rewards.

HPC without coding in MPI is possible, but only if your problem fits into one of several high level frameworks.

What happens when large-scale forces re-think the traditional solution? The shipping container has become the new supercomputer case.

By exploiting frictionless deliverables, the real story of SGI can be told through architected and integrated convergence

Aside from a new processor for cluster vendors to sell, the Nehalem represents a more subtle change in the market.

Yet another multicore rant. This one is triggered by the recent Multicore Expo.

Determining how fast your application will run on multi-core based systems all depends, And, it may not depend on you.

Relax. It is just a catchy headline to draw your attention to some classic insights into the HPC cluster market.

A simple game gives some insights into the complex uses for clusters and cores.

Did you know there are two projects that can give Ethernet a performance boost?

Would a Cluster By Any Other Name Be As Cool

Can HPC be more fun? Maybe a little more intelligence and graphics can put a smile on your face.

In the big picture HPC hardware is a small part of the economic equation. What are the big parts?

Setting expectations in a fast moving and fast computing market sector.

Is the HPC market big enough to drive new products and processors?

This week we jump ten years into the future to see how it all plays out.

This week we look at some preliminary HPC econimy survey numbers and intoduce a chance for you to smackdown the HPC experts

Open Discussion: Are the experts to be believed?

This week it’s your turn. How has the economy effected you HPC plans for next year? You are invited to participate.

A snapshot of the HPC market from IDC and the dreaded “wall” is here.

Back from SC08. Recovery from the HPC discovery is in order.

Live from SC08 — from the fast, to the small, to the piano bar, Doug remembers most of it.

Cluster Administration is possible and even easy if you focus on the basics.

How to rub elbows with the crew who started it all (and get some free beer)

Travel with Linux Magazine’s HPC editor as he finally learns why everyone is fussing over the the IBM iDataPlex.

Since we are already talking about packaging, let’s consisder those forgotten breakthroughs that help make it all possible.

The case for a personal cluster case. Can HPC growth be enhanced with only a few pieces of bent metal?

Today machines manage what we cannot. Are we dependent upon results or processes we do not understand?

The recent AMD split seems to be a sign of the times. Is sharing the new business model?

Another voice of concern over parallel programming. Plus a wild idea.

A journey into the heart of Wall Street HPC. It is still ticking.

HPC is just beginning to warm up to the idea of green computing. But can green give you a faster, better and cheaper high-performance cluster?

Multi-cores may come in varying and odd numbered sizes. Once again, software needs to adapt.

A grand experiment has begun. As protons collide, data flies around the globe landing in a cluster near you.

Not only does green HPC save money and reduce power usage, it also increase reliability.

How does one manage really big clusters? Perhaps nature can give us a clue.

Do we need software standard for clusters? Future software may make standards obsolete.

Cluster training for both student and teacher. Plus, re-learning a big lesson the hard way.

Cloud Computing: Revolutionary technology for high performance computing or partly cloudy with a chance of “we’ve heard this one before?”

Referential transparency — whatever that means — and the path forward.

Borrowing WiFi, wrapping up vacation, and seeking enlightenment through Erlang.

Tell me more, tell me more…

Is Erlang a Holy Grail for the multi-core/parallel developer? Doug Eadline begins to build his case.

So you think you’re a cluster vendor? You might want to watch how you toss that term around Mr. Eadline.

A trip down memory (addressing) lane for parallel programming.

Now with 100% less calculus.

Parallel fundamentals, what constitutes an actual parallel program, and why some applications may or may not run faster on multi-core systems.

Before tucking into that next project, developers really need to start asking themselves, “What’s this going to cost me?”

It is time to get serious about this multicore thing. No, for real, this time.

In my experience, the open approach, promotes open discussion, open experimentation, open solutions, and rapid growth. If you were looking for a market where the concept of “give a little and get a lot” works, you have arrived.

This week I’d like to take a look at the latest survey results. While the participation was not all that I wanted, it is enough to make sufficiently vague statements about the HPC cluster market.

What can we learn from the ants and bees? Perhaps something we can take something from the ants that may be helpful for clustering. If nodes were cheap and plentiful, then who cares? It would be kind of like stepping on ants: there always seem to be more.

Trying to get a handle on the HPC community and market has always been difficult. The professional market forecasters seem to paint a rosy picture for HPC over the next five years. But, when I talk to people in the market, I often get a different take.

Doug Eadline takes a break from his ranting about multi-core CPUs to rant about another technology that gives him fits: Virtualization.

It’s time for the yearly batch of retrospectives and predictions. Count me in! Let’s see, the big thing of 2007? Well, that had to be multi-core. And, the big prediction for 2008? Why that would be multi-core, once again. There, I’m done. Enjoy your year.

As 2007 fades away, I thought I would reflect on some of the HPC events of the last twelve months. Having thought about it, though, nothing really stands out in my mind as a big breakthrough or new paradigm shifting technology.

With all due respect to Forest Gump, defining fast is becoming a bit harder these days. And, yes, it has to do with multicore.

No matter how you cut it, coding for multicore is really just parallel programming.Doug Eadline explains the differences between OpenMP and MPI, when it’s smart to use existing code and when it’s time to rewrite an application to scale better on multicore systems.

Earlier this year, my wife and I decided to finish our basement. Great! I thought I could finally set up a real office. I had just one thing to do before my office would become a reality — deal with the ghosts of systems past.

I am standing in the middle of SC07 (Supercomputing 2007). SC07 is THE HPC event of the year. 318 exhibitors have made the trek to Reno, Nevada for SC07, and scores of attendees are here for the week-long conference. If you’re attending the show, you’re probably not reading this because you’re either completely exhausted, back-logged, depressed from losing your money at the casinos, still trying to get your shampoo back from the TSA agent at the airport, or some combination of the above.

Harnessing the power of multicore processors is one of the largest challenges facing the computer industry today. Here we look at the challenges and some of the programming methods we can use to solve the problem.

I find Pablo Picasso’s famous response on computers, “Computers are useless. They can only give you answers,” interesting and provocative. I also believe there is a grain of truth in that statement — namely, that it’s really important to ask the right questions of computers. I have a hard time with the useless part, however.

When comparing CPUs, you have to compare apples to apples. Doug Eadline compares the performance of AMD Opteron and Intel multicore processors to see which CPUs provide the best performance per core.

Back in the good old days of single core processors, when HPC clustering was in its infancy, getting the application as close as possible to the hardware was very important. In many cases, it still is. Communication between nodes could take place through the operating system by using TCP/IP or outside the OS using a userspace zero-copy protocol. With the exception of pinning down memory, the userspace protocol totally removes the OS from the communication. The result of userspace communication is better application performance thanks to better latency and throughput.

A story floating around the Internet recently claims that the Storm email worm has created the world’s largest supercomputer. I believe the genesis of this claim was this post on a security Web site. Are you amazed? Do we need James Bond to ferret out the evil villains? Hardly. Perhaps Austin Powers can handle this one.

As vendors strive for faster processors and denser systems, power and cooling has become a major issue for the HPC market.

Welcome to the NYCA-HUG

Explicit parallel programming presents special challenges for software developers. Now a new group of languages are coming online to address the compounded problem of multi-core processors on high-performance clusters.

Every time I talk about multi-core, I seem to start out with something like “back in the day” or “when things were much simpler,” or some such lament. Now prepare yourself for a stunning bit of insight. Cue music.

HPC cluster optimization is often simple. Avoiding assumptions is hard.

Clusters are getting larger, multi-core adoption plods along, and other findings from our recent HPC micropolls.

There I admit it. There are certain things that send me into long rants when it comes to High Performance Computing (HPC). (We’ll skip the non-HPC issues for now). I’ll bet you have issues as well. Those things that just bug you about the state of HPC clusters. Admit it, you do. There, don’t you feel better?

FLOPS are dirt cheap right now. How excited should you really be though?

In June of 2006 the Sandia National Laboratories’ 8960-processor Thunderbird Linux cluster was number 6 on the Top500 list. The system logged 38.3 TFLOPS and I’m guessing dimmed the lights a bit when it was running. Skip ahead to November 2006, and while there was some reshuffling of the contenders, Thunderbird managed to stay at the number 6 spot by achieving 53 TFLOPS. What happened?

Now that all of the major processor vendors have introduced multi-core chips, the impact of this relatively new technology on high-performance computing should to be addressed. What will is the immediate impact on HPC application development? And what will “many-cores” ultimately mean for the future of the HPC cluster?

Just like there are “Urban Legends” that never seem to die, so it seems there are “Cluster Urban Legends” that persist even today. We have all seen or heard them. As a service to those entering the cluster HPC (High Performance Computing) community, we dispel some of the more popular tales. (Read: misconceptions.)

What’s stopping clusters from being useful tools?

Confronting multi-core anxiety and what the new processors mean for the future of commodity clusters.

Got performance? A simple test provides a peek into the AMD and Intel Dual-core processor designs.

Welcome to No Disk Nirvana

What’s on your nodes? Do you really need all that stuff? Uh, it depends.

In case you haven’t noticed, the high-performance computing (HPC) market is now ruled by the Linux cluster. And while Linux clusters have made serious number crunching affordable, this disruptive change still has perils. Unlike more traditional HPC methods, a cluster presents a myriad of variables and trade-offs to the cluster designer and end-user. However, whenever there are choices that aren’t completely right or wrong, there is an opportunity for the artist and engineer to shine in all of us.

A hard to swallow conclusion from the table of cluster.

Dynamic Parallel Execution: Loosing control at the high end.

Off to see the wizards… of high-performance computing.

Developers, as Led Zeppelin said, “Yes there are two paths you can go by, but in the long run, there’s still time to change the road you’re on…”

Two months ago, the Kronos “value cluster” set a new record for price-to-performance, yielding 14.53 gigaflops at the cost of $171 per gigaflop. But is that the best Kronos can do? Or can some additional investment of time and effort push the extremes a little further? Discover if Kronos hits the proverbial wall, learning more cluster optimization techniques along the way.

With the introduction of multi-core processors, parallel programmers face a tough decision.

Quick, hand me the open source “clue stick.”

Getting the most out of your cluster is always important. But how exactly is that done? Do you really need to dissect your code and analyze every instruction to get optimal performance? Do you need to build custom kernels? Not necessarily. By testing some basic assumptions, you may be able to eke ten-node performance out of an eight-node cluster. Here’s how.

What are cluster builders up to these days? Cluster maven peeks into some machine rooms.

Today’s basic building blocks are Intel and AMD servers and high-speed networks. Tomorrow’s toys? Let’s take a look.

Systems with multiple cores are just like clusters. But there’s good news, too…

Linux on high-performance computing clusters seems an obvious choice now, but it wasn’t a forgone conclusion when Thomas Sterling and Donald Becker used Linux to build the world’s first Beowulf cluster in 1999. Linux has come a long way since then. Learn why Linux has put “super” back into supercomputers.