SIMD Vectorization Speedup - Quant Trader Interview Question
Difficulty: Medium
Category: Algorithms & Data Structures
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Topics: SIMD, vectorization, AVX-256, performance, optimization
Problem Description
You are optimizing a high-frequency trading algorithm that involves computing dot products between a large number of portfolio weights and market data. You have 256 portfolio weights. You are considering using AVX-256 instructions for vectorization, which can process 8 single-precision floating-point numbers (floats) simultaneously. What is the approximate theoretical speedup you can expect over non-vectorized (scalar) code when computing the dot products?
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