High-Frequency Trading with C++ — Blog Update 🔗 Check out the live post on LinkedIn In the initial implementation, a new cluster was created each time new data was read from the simulator's data stream. I observed that this approach resulted in significant time consumption due to the repeated creation and deletion of clusters. To address this, I developed a method to reuse the originally created cluster, substantially reducing overhead. The method for this improved version is quite simple: the clusters are declared static from the beginning, allowing them to persist and be reused. Because of the nature of the clusters — they are implemented as Red-Black Trees — if there are not enough nodes to accommodate new data, the code simply adds additional nodes dynamically, allowing for seamless expansion. This optimization was applied while feeding ExSan with my market simulator, which mimics the asynchronicity of ...
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