Rps With My Childhood Friend V100 Scuiid: Work

import random, time from collections import Counter def rps_result(p1, p2): # 0 = tie, 1 = p1 wins, 2 = p2 wins if p1 == p2: return 0 if (p1, p2) in [(0,2), (1,0), (2,1)]: return 1 return 2 moves = [0,1,2] results = [] for _ in range(1_000_000): a, b = random.choice(moves), random.choice(moves) results.append(rps_result(a,b))

I was intrigued. Not just by the tech, but by the chance to play RPS with my childhood friend again — even if through a terminal. The NVIDIA Tesla V100 is not your everyday GPU. With 640 Tensor Cores, 5120 CUDA cores, and 32GB of HBM2 memory, it’s designed for AI training, molecular simulations, and massive parallel computing. Alex had access to a V100 node through his university lab. rps with my childhood friend v100 scuiid work

– Stands for Scalable Collision-Resistant Unique Identifier . It’s a distributed ID generation protocol used in high-throughput databases. Alex’s work required generating billions of unique IDs without overlap. He wanted to test randomness distribution… using RPS as a metaphor. import random, time from collections import Counter def

Twenty years later, we reconnected over an unusual project: integrating with a SCUIID workflow (Scalable Continuous Unique Identifier). What started as a nerdy experiment became a profound journey through memory, probability, and friendship. With 640 Tensor Cores, 5120 CUDA cores, and

“Still can’t beat me,” he said.

And that’s the truth of it: some things are better together. Rock Paper Scissors. Childhood friends. Even a V100 and a messy ID system.