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Explore a 25-minute conference talk from CppCon 2024 that demonstrates how modern C++ features are revolutionizing computational cancer research through stochastic tumor modeling. Learn how C++11's random number generation capabilities, C++17's parallel computing features, and the Eigen linear algebra library combine to create efficient cancer simulation tools. Discover how matrix operations in the Eigen library simplify mathematical implementations, making it easier to express complex stochastic cancer modeling processes. Gain insights into using std::discrete_distribution and std::exponential_distribution for random process simulation, and understand how parallel STL algorithms and task-based concurrency enable the massive-scale simulations needed to study cancer variability. Through practical examples in colorectal cancer research, understand how computational biology is emerging as a significant domain for modern C++ applications in scientific computing.
