Imagine you're trying to figure out why your machine learning model is running slowly. Is it because the GPU's math units are maxed out? Is memory bandwidth the bottleneck? Or is the whole thing waiting on data that hasn't arrived yet? Today, you basically have two tools for answering this, and both are unsatisfying.

The first is the roofline model, a beloved chart in computer architecture that plots your workload as a single dot on a graph, showing whether you're limited by compute or memory. It's elegant, but it squashes your entire program into one point — you lose all sense of when things happen.

The second option is profilers and traces, which show every tiny event over time. These are the opposite problem: you can see everything, but drowning in fine-grained data makes it hard to say "aha, this is the bottleneck for this phase."

This paper introduces campaign diagrams, a new visualization that sits between these extremes. The idea is to break a workload into meaningful phases — say, the attention phase versus the feed-forward phase of a transformer — and then draw each phase in a way that simultaneously shows:

• How much compute throughput it's using (are the math units busy?)
• How much memory bandwidth it's using (are the pipes to memory full?)
• The total volume of compute work and memory traffic (essentially, the area of each phase)
• The latency — how long the phase actually takes

All of this fits on a single figure. You can literally see a workload "march" through its phases and spot where the bottleneck shifts from compute-bound to memory-bound, or where a phase is stalling waiting on something.

The clever bit is that campaign diagrams preserve the intuition of a roofline (compute vs. memory as the fundamental axes of hardware efficiency) while restoring the missing dimension of time. If you're designing hardware, tuning a kernel, or trying to explain to your team why a particular chunk of code is slow, being able to point at a single picture that shows both "what resource is the limit" and "for how long" is genuinely useful.

It's the kind of tool that feels obvious in retrospect — a good sign that it fills a real gap.