Efficient processing of numeric algorithms is critical to the finance industry, from trading and risk management to collateral management and portfolio optimization. Much of this analysis employs numerical methods that are very computationally intensive. Large firms have datacenters packed with thousands of compute nodes dedicated to this task. The workload has become more taxing as market volatility increases, portfolios get more complex, and more trading desks incorporate risk information into their decision making, requiring shorter turnaround times for analysis.
One of the biggest disruptions in computing in recent years has been the growth of NAND flash memory as an enterprise storage medium. Flash has much lower latency than spinning disk and has is projected to continue dropping in price rapidly. Along with the growth in adoption has come a proliferation of form factors, from arrays to SATA cards, and even cards that fit in DIMM slots.
Tick data (deep, granular time series of market prices and transactions) is the lifeblood of trading in liquid markets. Some consider it "big data," while others consider it business as usual. But all consider it essential.
The need for speed in trading has not abated. Technology that minimizes latency is simply the "greens fee" to trade in liquid markets today. Without it, you just can't play.
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