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HPC Servers Right-Sized for Exchange Co-Location Deployments in High Frequency Trading

BillMannel a week ago Wednesday StorageExpert

Co-locating within an exchange data center allows HFT firms to significantly reduce latency and speed order execution. However, selecting the right hardware is crucial.

High-frequency trading (HFT) algorithms have forever altered the landscape of securities trading. It’s now a high-speed, high-stakes world where every millisecond matters, and executing trades faster than the competition translates directly to greater revenue for firms, brokerages, and exchanges.

To survive in the ever-hastening world of HFT, today’s traders look to exploit even the slightest speed advantages in order to improve their access to up-to-the-minute market pricing and reduce order processing times. Even a connection that is just one millisecond faster than a competitor’s is said to have the potential to boost an HFT firm’s earnings by up to $100 million per year. 

Co-location is one of the primary tactics that traders use to gain an advantage. HFT firms positiHPCServers_FSI_blog.jpgon their servers in the same data center as the exchanges, enabling them to access market data feeds a few milliseconds before the rest of the investing community and achieve the lowest possible levels of latency. Reducing the amount of physical cable that data must travel over to reach its destination also helps improve network connectivity, as LAN bandwidth is faster, safer, and more reliable than WAN.  

Co-location has become so popular that the worldwide co-location market is expected to generate $36.1 billion in annual revenue by the end of 2017, up from $22.8 billion in 2015. This demand for co-location space is prompting exchanges to rapidly expand the size of their facilities and charge high premiums for such sought-after data center real estate. However, the cost and complexity of deploying compute infrastructure in close proximity to exchanges can sometimes make co-location beyond the expertise and budgets of smaller HFT houses.

Selecting the right hardware becomes important when considering a co-location deployment. Here are some factors to consider:

  • Space Constraints: Particularly when space comes at a high premium, a small footprint is crucial to economize on space. High-density servers not only offer significant capital and operating expense savings but also pack a lot of performance and workload capacity into a small area.
  • Energy-efficiency: Hardware configurations right-sized for the standard power capacities of exchange co-location facilities allow for easy deployment, while energy-efficient server platforms boost cost savings.
  • Flexibility: Flexible server configurations promote easy co-location or space-constrained deployments, and enable firms to select a HPC cluster that satisfies their needs and co-location budget.

The HPE Trade and Match Server family is designed to allow firms to easily take advantage of co-location services. The HPE Apollo 2000 System is density-optimized and purpose-built to fit within a traditional data center environment, meaning firms can streamline their co-location efforts while gaining the processing power necessary to execute more quickly than the competition.

Co-locating within an exchange data center allows HFT firms to significantly reduce latency and speed order processing, however many exchanges have strict space and power requirements. Selecting the right hardware for a co-location deployment is crucial to enable firms to achieve an edge over the competition and grow revenue. 

Don’t risk losing your edge in one of the most data-intensive industries – follow me on Twitter @Bill_Mannel to learn more about HPE’s HPC trading solutions for financial services firms.

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About the Author

BillMannel

As the VP and GM of HPC and Big Data and IoT Solutions for HPE Servers, I lead our worldwide strategy and execution in the market’s fastest growing category including the HPE Apollo, HPE Moonshot and our newest product designed for computing at the Edge, the Edgeline server series.

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