A Mental Model of TPUs for Performance Engineering
A visual mental model for understanding TPU architecture and how it relates to ML workloads.
Pretraining SmolLM-360M on a single A100 GPU within a 30-hour window, focusing on feasibility analysis, throughput measurement, and hardware efficiency optimization.
A visual mental model for understanding TPU architecture and how it relates to ML workloads.
Exploring whether language model agents can enhance the performance of other LLM agents through a meta-benchmark approach.
Analyzing the dot product operation through the roofline model on NVIDIA H100 GPU hardware.