Armadillo’s lazy evaluation is beneficial in situations where large matrices are involved, and computational efficiency is crucial. It helps optimize performance by delaying the actual computation until it’s absolutely necessary, allowing for potential simplifications and reduced memory usage.
Lazy evaluation works by creating expression templates that represent operations on matrices without performing them immediately. This enables Armadillo to combine multiple operations into a single one, minimizing temporary storage requirements and redundant calculations.
For example, when multiplying three matrices A, B, and C, instead of computing (A * B) * C with two separate multiplications, Armadillo can perform a single multiplication using lazy evaluation: A * (B * C). This reduces the number of required operations and avoids creating an intermediate result matrix.
