# SIMD Vectorization in Modern CPUs SIMD (Single Instruction, Multiple Data) vectorization is a technique employed by modern CPUs to process data in parallel, enhancing computing performance. A standard CPU processes data sequentially, i.e., one operation at a time. With SIMD, the CPU can perform the same operation on multiple data points concurrently. This is particularly useful in applications that involve repetitive computations on large arrays of data, such as image processing and machine learning algorithms. ## How Does SIMD Work? Consider processing an array of integers. Traditionally, a CPU would take each integer and perform operations one by one. SIMD, however, allows the CPU to take a chunk of the array and process it in one go. This chunk is known as a vector, hence the term vectorization. Here's a simple C++ code snippet showing how SIMD works: ```cpp #include
// for AVX void add(int* a, int* b, int* c, int size) { for(int i=0; i