The Pivot Point: Rewriting the Dispatcher Loop for PI-Controlled GPU Dispatch

In the iterative refinement of a complex GPU pipeline scheduling system, there comes a moment when theory must meet practice—when the carefully designed controller struct must be wired into the actual execution path that governs how work flows through the system. Message [msg 3447] captures exactly this moment. It is deceptively brief: the assistant simply states "Now the big one — rewrite the dispatcher loop:" and issues a read call to examine the current dispatcher code. But this short utterance marks the critical transition from component implementation to system integration, where the PI-controlled dispatch pacer—built over the preceding messages—must be fused with the live control loop that drives GPU proving.

The Context: A Long Road of Iterative Control Design

To understand why this message matters, one must appreciate the journey that led to it. The team had been wrestling with GPU underutilization in the cuzk proving engine for some time. The root cause had been identified earlier: a zero-copy pinned memory pool resolved the H2D transfer bottleneck, but the dispatch logic—the mechanism that decides when to send synthesized partitions to the GPU—remained unstable. The initial approach used a semaphore-based reactive throttle that limited total in-flight partitions, but this proved inadequate because it failed to maintain a stable pipeline depth. The user's critique was precise: the semaphore constrained the total in-flight work rather than targeting a specific queue depth of synthesized partitions waiting for the GPU.

The assistant then implemented a P-controller (proportional-only control) that replaced the semaphore with a Notify-based two-phase loop: wait for a GPU completion event, then dispatch the full deficit in a burst. This was designed to intentionally overshoot and converge on a steady state. But the first deployment (cuzk-pctrl1) proved too aggressive, instantly filling all allocation slots. A dampening factor was added (cuzk-pctrl2), capping burst size at max(1, min(3, deficit * 0.75)), yet the system remained unstable. The root cause was the deep synthesis pipeline: with single synthesis taking 20–60 seconds depending on contention, the feedback signal—the number of items waiting in the GPU queue—was both noisy and severely delayed.

The user then proposed a more sophisticated approach: a PI controller (proportional plus integral) operating on a smoothed signal like an Exponential Moving Average (EMA) of the waiting count or GPU consumption rate. This is where message [msg 3447] enters the story.

What the Message Actually Says

The message itself is remarkably concise:

Now the big one — rewrite the dispatcher loop: [read] /tmp/czk/extern/cuzk/cuzk-core/src/engine.rs

It then displays the content of the file starting at line 1354, showing the existing dispatcher code that creates a channel for synthesis dispatch. The assistant is reading the current implementation to understand exactly what needs to be replaced.

This brevity is telling. The assistant has already done the heavy intellectual work in the preceding messages: designing the DispatchPacer struct ([msg 3431]), adding the gpu_completion_count atomic counter ([msg 3436]), and wiring the counter into the GPU finalizer ([msg 3444]). What remains is the most delicate part—rewriting the live dispatcher loop that controls the actual flow of work. The phrase "the big one" signals recognition that this is the riskiest and most consequential change in the entire pacer implementation.

Why This Message Was Written: The Motivation

The assistant wrote this message because the dispatcher loop is the central nervous system of the GPU pipeline. All the prior changes—the DispatchPacer struct with its EMA smoothing, PI gains, and bootstrap logic; the atomic counter shared between GPU finalizers and the dispatcher; the wiring of counter increments into completion paths—are inert without the loop that uses them. The pacer struct exists as a pure computation unit: it can calculate intervals, update EMAs, and compute PI corrections, but it has no agency. The dispatcher loop is where the pacer's decisions become actions.

The motivation is threefold. First, the existing dispatcher loop was designed for the burst-based P-controller, which dispatched in batches triggered by GPU completion events. The new pacer requires a fundamentally different loop structure: timer-based pacing with steady per-item dispatch, a bootstrap phase that dispatches the target number of items upfront, and a PI-controlled steady-state phase that adjusts the dispatch interval based on smoothed feedback signals. Second, the loop must integrate the new shared state—the gpu_completion_count atomic and the gpu_done_notify—into a tokio::select! that races a pacing timer against GPU completion events and shutdown signals. Third, the loop must handle edge cases that the pacer struct alone cannot: what happens when the work queue is empty? When budget acquisition blocks? When the system is in bootstrap versus steady-state?

Assumptions Embedded in the Rewrite

The assistant makes several assumptions in approaching this rewrite. The most significant is that the PI-controlled pacer will actually stabilize the system where the P-controller failed. This is an assumption grounded in control theory: integral action eliminates steady-state error, and EMA smoothing filters out the noise that made the raw waiting count an unreliable signal. But it remains an untested hypothesis until the code runs on real workloads.

Another assumption is that the bootstrap phase—dispatching target items at a fixed spacing before any GPU completions occur—is the right startup strategy. The assistant's reasoning (visible in [msg 3429]) shows careful consideration: with 20–60 second synthesis times and ~1 second GPU times, the system needs roughly 20–60 concurrent syntheses to keep the GPU fed, but the target queue depth is only 8 items. The bootstrap phase must quickly establish this baseline without overshooting into memory exhaustion.

The assistant also assumes that the PI gains (Kp=0.1, Ki=0.01 in the initial design) are conservative enough for the 20–60 second pipeline delay. This is a non-trivial control theory problem: with such long delays, even small gains can cause oscillation if the integral term winds up during the initial transient. The assistant's reasoning shows awareness of this, noting that "the PI gains need to be very conservative" and that "the feed-forward (GPU rate matching) does the heavy lifting; PI just nudges around it."

Input Knowledge Required

To understand this message, one needs knowledge of several domains. First, the architecture of the cuzk proving engine: the dispatcher loop lives in engine.rs, it manages a priority work queue, a bounded channel for synthesis dispatch, a memory budget system, and GPU worker tasks that consume synthesized partitions. Second, the control theory concepts: proportional-integral control, exponential moving averages, integral anti-windup, and the challenges of controlling systems with long feedback delays. Third, the Rust async programming model: tokio::select!, Notify for event signaling, tokio::time::sleep for timer-based pacing, and the intricacies of cancel-safety when futures are dropped. Fourth, the specific history of this project: why the semaphore failed, why the P-controller oscillated, and why the user proposed a PI controller with EMA smoothing.

Output Knowledge Created

This message creates knowledge about the intent and structure of the upcoming rewrite. It tells the reader (and the user) that the assistant has completed the component-level changes and is now ready for the integration phase. The read call exposes the current dispatcher code, which serves as a shared reference point for the subsequent edit. The message also implicitly communicates the assistant's assessment of risk: "the big one" signals that this is the most consequential change, one that could break the pipeline if done incorrectly.

The subsequent messages ([msg 3448] through [msg 3457]) show the rewrite unfolding: the assistant replaces the entire dispatcher block, fixes a brace mismatch that causes a compilation error, verifies a clean compile, builds a Docker image tagged pacer1, and extracts the binary for deployment. The rewrite is successful—the code compiles, the image builds, and the pacer is deployed.

The Thinking Process: What the Reasoning Reveals

The assistant's reasoning in the preceding message ([msg 3429]) provides deep insight into the thinking behind this rewrite. The assistant explicitly works through the control theory: "With a pure delay of 20-60s in the system, the PI tuning becomes quite conservative — Kp around 0.017 and Ki around 0.00014 with a 30s delay and 1s base interval." These are extremely small gains, reflecting the assistant's understanding that aggressive correction in a delayed system leads to oscillation.

The reasoning also reveals a tension between theoretical purity and practical engineering. At one point the assistant writes: "Actually, I'm overthinking the control theory here. What the user really needs is straightforward: a pacer that maintains a steady dispatch rate, PI control that gently adjusts it, and an EMA filter to smooth out noise in the waiting signal." This self-correction is characteristic of experienced engineers who know when to stop optimizing and start building.

The assistant also grapples with the bootstrap problem: how to initialize the system before any GPU timing data exists. The reasoning shows multiple iterations: first considering a fixed 100ms bootstrap interval, then realizing this would overshoot during the 10-second synthesis phase, then settling on a bootstrap counter that dispatches exactly target items upfront before waiting for the first GPU completion. This is visible in the message flow where [msg 3450] fixes the bootstrap path to include a timer sleep, preventing instant burst dispatch.

Conclusion

Message [msg 3447] is the hinge point of the entire pacer implementation. It is the moment when design becomes deployment, when theory becomes code, when the carefully crafted DispatchPacer struct must prove itself in the live control loop. The message is brief—a single sentence and a file read—but it carries the weight of all the preceding analysis, all the control theory reasoning, all the failed attempts with semaphores and P-controllers. It is the pivot point where the system either stabilizes or reveals yet another flaw in the design. In the end, the rewrite compiles cleanly and deploys as pacer1, marking the beginning of a new chapter in the GPU pipeline scheduling saga—one that would eventually require further refinement with a synthesis throughput cap, but that nevertheless represented a genuine advance over the burst-based approaches that came before.