You might ask: Why document this? Why v100? Why SCUIID work?
Because RPS with my childhood friend is not about winning. It’s about continuity. Every throw is a timestamp of who we were:
SCUIID work turned ephemeral hand gestures into shared history. v100 became a monument to a friendship that refused to fade despite college, jobs, moves, and disagreements far bigger than a hand game.
Rock Paper Scissors (RPS) is often dismissed as a child’s game of chance. But when you play RPS with my childhood friend, it becomes a language—a ritual, a battlefield, and a time capsule. This article chronicles our journey through version 100 (v100) of our personal RPS league, complete with what we call SCUIID work—a quirky, homegrown system for tracking matches, verifying outcomes, and settling disputes that would make any esports referee proud.
If you’ve ever wondered how two grown adults can spend decades perfecting a three-gesture combat system, read on. rps with my childhood friend v100 scuiid work
My childhood friend, Alex, and I met at age seven on a cracked asphalt playground. We couldn’t agree on who would go first on the slide. His solution? “Rock Paper Scissors, best of one.” I lost. But from that moment, RPS with my childhood friend became our default arbitration mechanism.
By age ten, we had formalized rules:
No spreadsheets. No referees. Just trust—most of the time.
We didn’t physically play every round, of course. But we scripted “players” based on childhood memory: You might ask: Why document this
Watching the V100 crunch through millions of rounds — seeing the win rates converge to 33.33% — was oddly comforting. It was like proof that even in perfect randomness, our childhood rivalry was fair.
We added a nostalgia feature: every 1 million rounds, the program printed a memory from our actual childhood RPS games.
"Round 1,000,000: Alex used scissors to cut my paper – just like 3rd grade art class."
That broke me. In a good way.
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. SCUIID work turned ephemeral hand gestures into shared
Why use a V100 for Rock Paper Scissors? Because we weren’t just playing a single game — we were simulating 100 million rounds of RPS to test SCUIID’s entropy distribution.
Each round of RPS requires three things:
Running 100M rounds sequentially is slow. But on a V100, with CUDA-optimized kernels, we could simulate 10M rounds per second. That’s the power of parallelization.
