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Medium · low_latency · Quant Developer interview question · simd, avx2, fx-conversion, low_latency, vectorization, double-precision
Low-latency trading systems often use SIMD (Single Instruction, Multiple Data) to perform parallel computations on batches of data, a critical optimization for performance-sensitive code. A common application in quantitative finance is converting prices from multiple currencies to a single base currency for pre-trade risk checks. This is achieved by broadcasting a single FX rate and multiplying it against a vector of prices in a single CPU instruction, significantly improving throughput over sca
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