Category Archives: Computational Finance

Future trends in HPC, part 1

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As we near the end of 2011, we take a moment to reflect on the past year. It’s been a busy year for IT across virtually all verticals, from mobile and search to enterprise servers and cloud computing. When we attended HPC360 a few weeks ago, we had the pleasure to attend a keynote presentation by Addison Snell, CEO of Intersect Research in which he discussed the most important trends in high performance computing (HPC).

HPC is an exciting and growing industry that ICC has been moving into the past couple years. The traditional HPC space revolved around high-end research facilities particularly in science and engineering. However, with each year technological innovations and tailored systems such as our Supermicro GPU Simcluster have brought the realm of HPC closer to reality for many small/medium-sized business and organizations.

In this 2-part series we will look at the top 10 future trends in HPC from Intersect360′s research, coupled with our own analysis and thoughts. No better way for us computer nerds to close the year right? Let’s get started.

Top 10 HPC Trends for 2012 and Beyond

Future Trends for High Performance Computing Image

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HPC360 Conference Recap

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HPC360 Flyer

We just returned from R Systems HPC360, a conference on high performance computing down in Champaign, Illinois which brought together leading industry professionals, academics, scientists, and enthusiasts.

The conference was titled HPC360 “Innovation through Modeling and Simulation”. The event took place at the i Hotel and Conference Center in Champaign, hosted by R Systems and sponsored by a number of companies including Dell, AMD, Intel, and yours truly, ICC!

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Microsoft HPC Server 2008 R2 – cool new features

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Yesterday, at an HPC conference for the financial industry, Microsoft announced an update (R2) for Windows HPC Server 2008. Aside from offering new features that will take advantage of innovations in cloud computing, Microsoft claims that this update will make HPC Server 2008 less expensive to operate than Linux.

The reasoning, according to Microsoft, is that Linux requires much expensive expertise to use while the Windows interface is familiar to just about anybody in computing. Moreover, as Computer Reseller News reports, a Microsoft-funded study found that Windows HPC Server is 32-51% less expensive in the long-term than a Linux HPC solution.

There are several other features about which the new update of Microsoft HPC Server 2008 can boast. First, number crunching large data sets in Excel (a popular method with the financial computation industry) has become a lot more efficient.

This is partly due to a second major innovation: the ability to outsource computing to more powerful clusters from one’s Windows workstation. A series of calculations that would have taken two hours to complete before, writes HPC Wire, can now take less than two minutes.

Finally, the new update also takes advantage of cloud computing from the other direction: not one powerful HPC cluster assisting individual workstations, but rather many PCs volunteering their time to help compute a few data-intensive calculations.

This is the same idea as SETI@home or Einstein@home: any PC user can allow their computer to be used as part of a cloud to perform others’ calculations when it is not needed by the user herself.

With these impressive additions to Windows HPC Server 2008, Microsoft seeks to chip away at Linux’s lead in the HPC market.

Yesterday’s (May 6) stock plunge and computational finance

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For those following financial news, yesterday was a crazy day on the stock market. Financial markets around the world have already been on a perpetual roller coaster ride because of sagging economic growth in Europe, especially in Greece. But yesterday, the DOW took its single largest plunge in history – an almost 1,000 point-loss (about 10% of the market) in less than half an hour.

Analysts are straining to figure out what exactly caused this fall. Rumors and conjectures have been swirling around the media for lack of better information. Although the stock market recovered most of the value it had lost before closing on May 6, people rightly want to discern what were the causes of the brief crash.

Tim Paradis of the Associated Press reports some of the current explanations for yesterday’s price fall. One idea is that a trader mistakenly entered $16 billion instead of $16 million into a sell order. Another possible trigger is a mis-listing of the price of Procter & Gamble stock, which caused massive selling of that stock and a subsequent 37% drop in its price.

After listing these theories, Paradis concludes,

Whatever started the selloff, automated computer trading intensified the losses. The selling only led to more selling as prices plummeted and traders tried to limit their losses.

“I think the machines just took over. There’s not a lot of human interaction,” said Charlie Smith, chief investment officer at Fort Pitt Capital Group. “We’ve known that automated trading can run away from you, and I think that’s what we saw happen today.”

In a nutshell, when financial computers detected a significant drop in the stock market (be it from the erroneous $16 billion dollar sell order or from mist-quoting Procter & Gamble stock price), they saw this as a sign that stocks were losing value. Then, they automatically sold shares, which caused even more devaluation and selling.

While it is true that inadequate computational models may have been partly to blame for both the recent recession in general and yesterday’s price plunge in particular, it is important to keep this criticism in perspective.

Computational finance is still an industry in its infancy, and like with all human devices that fail at some time, it’s no use blaming the device for the failure. We should blame human error. For example, if a bridge collapses somewhere, we don’t blame the physical structure itself; we seek to find the faults in our own engineering plans that caused the accident.

Computational finance, using mathematical algorithms to make sense of the stock market, offers much promise in making sense of the seemingly-chaotic world of financial trading. As computers grow more powerful, they will be able to answer the most difficult questions in finance, and the stock market may cease to seem so arbitrary. This industry should be allowed to develop, but with sufficient checks in place and smarter algorithms to prevent shocks like the one that happened yesterday.