OOP's dirty secret: your elegant objects are just cache-missing memory shrapnel tanking app speed and burning through VC runway

A recent article highlights the importance of Data-Oriented Design (DOD) in optimizing code performance, particularly in memory-bound applications. The key issue is that object-oriented design scatters data across memory, leading to cache misses and slowing down the CPU. In contrast, DOD organizes data contiguously, leveraging cache lines, prefetching, and SIMD instructions. This approach can result in significant performance gains, with the article citing examples of 2-5x speed improvements. The concept is not new, but its application is crucial in modern computing, where the gap between CPU and RAM speeds is significant, with the CPU being 100-1000 times faster. By understanding how hardware processes data, developers can write more efficient code, and DOD is already being applied in various industries, including game development and scientific computing, with libraries like NumPy and Pandas relying on contiguous arrays to achieve high performance.