Python Random Number Generation Performance with the Intel Python Distribution

Jeff compares a stock random number generation for 10,000 numbers, then compares it to the random Intel version. Then Jeff brings in some timers to generate 10,000 random numbers, but then swaps in several different pseudo random number generators, then tests their performance relative to the Mersenne Twister basic random number generator, the MT19937. He also uses the Wichmann–Hill algorithm, the Philox Block cipher algorithms, the MT2203, the SIMD optimized Mersenne Twister, etc. to compare other performances, Then compares how much faster or slower these are to the Mersenne Twister.