When a closed-form solution does not exist or is not worth finding, random sampling is the most practical path forward. This post covers the core theory of Monte Carlo estimation — convergence, variance reduction, PRNG discipline — and applies it to portfolio Value at Risk, infrastructure reliability, and capacity planning, with a full Python walkthrough using numpy.
Simulation
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Monte Carlo Methods: Simulating Your Way Out of Hard Math -
Verilator Deep Dive: Open-Source Simulation That Can Actually Replace Your Commercial Tool Modern Verilator as a genuine alternative to commercial RTL simulators — compiling SystemVerilog to cycle-accurate C++ that runs 10-100x faster — covering what it now handles well, its limits, and how to wire up testbenches.