Measured GPU systems work

Evidence-backed GPU systems work across serving infrastructure and kernel optimization. Each project page carries the story, the architecture calls, and the measured runs behind them.

Serving infrastructure · 7 experiments · 9 decisions

GPU Inference Decision Lab

An EKS/vLLM lab that turns serving measurements into architecture decisions for admission, autoscaling, context limits, scheduling, and quantization.

100% queued delivery across burst and spike-to-zero admission runs
1.20 req/s long-context knee repeats with 36.8s p95 queue delay
FP8 KV rejected on the current g4dn/vLLM path

View project GitHub

Kernel optimization · 9 experiments · 9 decisions

CUDA Kernel Lab

A CUDA/Triton optimization lab organized around profile-driven kernel work for LLM-shaped primitives across A10G and H200.

115 operator rows plus 27 decode replay rows on A10G
H200 matmul rows keep best standard Triton around 88-90% of PyTorch/cuBLAS
RMSNorm fp16 reached 5.901x over the PyTorch baseline

View project GitHub