Fast, Low-Memory Algorithm for Construction of Nanosecond Level Snapshots of Financial Markets

We present a fast, low-memory algorithm for constructing an order-by-order level snapshot of financial markets with nanosecond resolution. This new implementation is 20-30x faster than an earlier version of the code. In addition, since message data are retained only for as long as it they are needed, the memory footprint is greatly reduced. We find that even the heaviest days of trading spanning the NASDAQ, NYSE and BATS exchanges can now easily be handled using compute nodes with very modest memory (~ 4 GB). A tradeoff of this new approach is that the ability to efficiently manage large numbers of small files is more critical. We demonstrate how we can accommodate these new I/O requirements using the solid-state storage devices (SSDs) on SDSC's Gordon system.