The Art of the Systematic Sweep: Tuning Partition Workers in a SNARK Proving Engine

In the high-stakes world of Filecoin proof generation, every second counts. A Groth16 proving pipeline that consumes ~200 GiB of peak memory and runs across CPU and GPU must be tuned with surgical precision. This article examines a single message from an opencode coding session — message index 2275 — where an AI assistant executes a bash command to restart a distributed proving daemon with a specific configuration parameter. On its surface, the message is mundane: a daemon startup with a log line confirming SRS preload has begun. But in context, it represents a critical juncture in a systematic performance optimization campaign, one that reveals the iterative, debugging-heavy reality of real-world systems engineering.

The Message

The subject message is a straightforward bash invocation:

[assistant] [bash] cd /home/theuser/curio/extern/cuzk && nohup ./target/release/cuzk-daemon --config /tmp/cuzk-sweep.toml > /tmp/cuzk-sweep-pw15.log 2>&1 &
echo "PID=$! pw=15"
sleep 5 && tail -2 /tmp/cuzk-sweep-pw15.log
PID=3449867 pw=15
[2026-02-19T01:44:06.883156Z]  INFO cuzk_core::engine: preloading SRS via SrsManager (Phase 2) circuit_ids=[Porep32G]
[2026-02-19T01:44:06.883256Z]  INFO cuzk_core::srs_manager: loading SRS from disk circuit_id=porep-32g path=/data/zk/params/v28-stacked-proof-of-replication-merkletree-poseidon_hasher-8-8-0-sha256_hasher-82a357d2f2ca81dc61bb45f4a762807aedee1b0a53fd6c4e77...

The assistant starts the cuzk-daemon — the core proving engine for the cuzk SNARK pipeline — with a configuration file that sets partition_workers = 15. It captures the PID, sleeps briefly to let the daemon initialize, and tails the log to confirm startup succeeded. The log shows the SRS (Structured Reference String) manager beginning to load the porep-32g parameters from disk, a multi-gigabyte preload that takes significant time.

The Context: A Systematic Performance Sweep

To understand why this message exists, we must step back. The user — a developer working on the cuzk SNARK proving engine for Filecoin's Proof-of-Replication (PoRep) — had just received the results of a major architectural change. The assistant had implemented and committed Phase 8: Dual-Worker GPU Interlock (commit 2fac031f), which narrowed a C++ static mutex to cover only the CUDA kernel region, allowing two GPU workers per device to interleave CPU and GPU work. The results were impressive: GPU efficiency hit 100.0%, and throughput improved by 13–17% over Phase 7.

But one question remained: what is the optimal partition_workers setting? This parameter controls how many partition synthesis tasks run concurrently. Too few, and the GPU starves for work. Too many, and CPU contention from parallel synthesis starves the GPU's preprocessing threads. The assistant had already identified that partition_workers=30 regressed badly (60.4s/proof vs 44.0s/proof at pw=20), confirming that excessive parallelism hurts. But the sweet spot remained unknown.

The user's instruction was terse: "sweep 10,12,15,18,20" ([msg 2248]). This is a classic engineering practice — systematically varying a parameter across a range to empirically determine the optimum. The assistant dutifully created a todo list and began executing.

Why This Message Was Written: Recovery and Persistence

By the time we reach message 2275, the assistant has already completed pw=10 (43.5s/proof) and pw=12 (43.5s/proof), both showing identical throughput. The pw=15 attempt, however, encountered operational difficulties. In message 2268, the assistant tried to combine pkill, config writing, and daemon startup into a single bash command — but the command timed out after 120 seconds, killing the entire pipeline. The sed substitution to change partition_workers = 12 to partition_workers = 15 never executed because the command was terminated mid-flight. The daemon never started.

This is a crucial moment. The assistant had to diagnose the failure: the config file still showed partition_workers = 12 ([msg 2259]), the log file for pw=15 didn't exist ([msg 2271]). The recovery required several steps: killing any lingering daemon processes, manually rewriting the config file with a heredoc instead of relying on sed, verifying the change persisted, and then starting the daemon in a separate, simpler command that wouldn't exceed the timeout.

Message 2275 is the successful execution of that recovery. The assistant has learned from the timeout failure and split the work: the pkill and config rewrite happened in earlier messages (<msg id=2273-2274>), and this message handles only the daemon startup with a built-in verification step (sleep 5 && tail -2). The output confirms PID 3449867 and the SRS preload beginning.

Assumptions and Decisions

Several assumptions underpin this message. First, the assistant assumes that the configuration file at /tmp/cuzk-sweep.toml correctly specifies partition_workers = 15. This assumption was validated in the preceding message ([msg 2274]) where grep partition confirmed the value. Second, the assistant assumes the daemon binary at ./target/release/cuzk-daemon is the correct, freshly compiled version with Phase 8 changes. Third, it assumes that the SRS preload will succeed — that the parameter file exists at the specified path and is uncorrupted. Fourth, it assumes that 5 seconds of sleep is sufficient to capture meaningful startup log output.

The decision to use nohup and background the process is deliberate: the daemon is a long-lived server that must persist across the benchmark session. The decision to redirect output to a per-configuration log file (/tmp/cuzk-sweep-pw15.log) enables later inspection and debugging. The decision to echo the PID and tail the log provides immediate feedback without requiring a separate polling command.

Input Knowledge Required

To fully grasp this message, one needs substantial context about the cuzk proving pipeline. The partition_workers parameter governs how many Groth16 partition synthesis tasks execute concurrently during proof generation. Each partition represents a portion of the circuit that can be synthesized independently before the GPU combines them. The SRS (Structured Reference String) is a large cryptographic parameter file — for porep-32g (32 GiB sectors), this can be tens of gigabytes — that must be loaded into memory before any proof can be generated. The SRS preload is a known bottleneck, taking significant time and memory.

The hardware context is also essential: this runs on a 96-core AMD Zen4 machine with an NVIDIA RTX 5070 Ti GPU. The partition_workers tuning is specific to this CPU-GPU balance. The benchmark methodology uses c=5 j=3 — 5 proofs with concurrency 3 — which stresses the pipeline with multiple overlapping proof requests.

The broader architectural context includes the Phase 8 dual-worker interlock, which allows two GPU workers to share a single GPU device by narrowing the C++ mutex scope. This means the GPU can be kept busy while one worker does CPU preprocessing and the other runs CUDA kernels.

Output Knowledge Created

This message produces a running daemon process (PID 3449867) configured with partition_workers = 15, listening on port 9820. The log confirms that SRS preload has initiated. This daemon will serve as the target for the upcoming benchmark, which will measure throughput across 5 proofs with concurrency 3. The result — 44.8s/proof, as revealed in subsequent messages — will contribute to the empirical dataset that ultimately identifies pw=10–12 as the optimal range.

The message also implicitly validates the recovery procedure: the assistant demonstrated that it can diagnose a failed daemon startup, correct the configuration, and successfully launch the daemon. This operational knowledge — that complex bash pipelines risk timeout termination and should be split into atomic steps — is itself a valuable output.

The Thinking Process

The assistant's reasoning is visible in the sequence of messages leading to this one. After the pw=12 benchmark completed ([msg 2267]), the assistant immediately attempted pw=15 by combining pkill, config writing, and daemon startup ([msg 2268]). When that command timed out, the assistant checked for the log file (<msg id=2270-2271>), found it missing, and correctly inferred that the command never executed. It then killed any remaining daemon processes ([msg 2272]), checked the config file ([msg 2273]), found it still showed pw=12, and corrected it ([msg 2274]). Only then did it attempt the daemon startup in message 2275.

This debugging chain reveals a methodical, hypothesis-driven approach: "The command timed out → the daemon probably didn't start → let me check the log → the log doesn't exist → let me check the config → the config wasn't updated → let me fix the config and retry." Each step narrows the problem space. The assistant also adapts its approach: instead of relying on sed (which failed because it was part of a killed command), it uses a heredoc to rewrite the entire config file, a more robust approach.

Conclusion

Message 2275 is a small but revealing snapshot of real-world systems engineering. It captures the moment when an AI assistant, after encountering and debugging an operational failure, successfully launches a critical benchmark configuration. The message itself is simple — a daemon startup with a log line — but the context transforms it into a story of systematic optimization, adaptive debugging, and the relentless pursuit of empirical data. The partition_workers sweep that this message enables will ultimately identify the optimal setting for a production SNARK proving pipeline, directly impacting the cost and throughput of Filecoin storage proofs. In the world of high-performance distributed systems, even a single bash command can carry the weight of hours of prior reasoning, debugging, and architectural insight.