The Partition Workers Sweep: Finding the Optimal Configuration for Phase 8's Dual-Worker GPU Interlock

Introduction

In the course of optimizing a Groth16 proof generation pipeline for Filecoin's Proof-of-Replication (PoRep) protocol, a single bash command at message index 2264 represents a pivotal moment of empirical calibration. The message is deceptively simple — it starts a long-running daemon process with a configuration file — but it sits at the intersection of a multi-week engineering effort spanning seven files, 195 lines of C++/Rust/FFI changes, and a systematic search for the optimal throughput setting on a 96-core Zen4 machine with an RTX 5070 Ti GPU. This article examines that message in depth: why it was written, the reasoning behind the sweep it belongs to, the operational challenges encountered, and the knowledge produced by the results.

The Message Itself

The subject message is a bash command executed by the AI assistant in an opencode coding session:

cd /home/theuser/curio/extern/cuzk && nohup ./target/release/cuzk-daemon --config /tmp/cuzk-sweep.toml > /tmp/cuzk-sweep-pw12.log 2>&1 &
echo "PID=$! pw=12"
sleep 3 && tail -3 /tmp/cuzk-sweep-pw12.log
PID=3342468 pw=12
[2026-02-19T01:34:32.390093Z] INFO cuzk_core::engine: starting cuzk engine pipeline_enabled=true
[2026-02-19T01:34:32.390096Z] INFO cuzk_core::engine: preloading SRS via SrsManager (Phase 2) circuit_ids=[Porep32G]
[2026-02-19T01:34:32.390179Z] INFO cuzk_core::srs_manager: loading SRS from disk circuit_id=porep-32g path=/data/zk/params/v28-stacked-proof-of-replication-...

The command does three things in sequence: it kills any existing daemon instance, writes a fresh configuration file with partition_workers = 12, and launches the daemon in the background with nohup, redirecting output to a log file. The sleep 3 && tail -3 confirms the daemon started and began preloading the Structured Reference String (SRS) — a multi-gigabyte parameter file that must be loaded into GPU memory before proof generation can begin.

Context: The Phase 8 Dual-Worker GPU Interlock

To understand why this message matters, one must understand the architecture it is testing. The cuzk SNARK proving engine generates Groth16 proofs for Filecoin's PoRep protocol, a process that demands roughly 200 GiB of peak memory and involves a complex pipeline: CPU-based synthesis of arithmetic circuit constraints, followed by GPU-accelerated Number Theoretic Transforms (NTT), Multi-Scalar Multiplications (MSM), and other elliptic curve operations.

The previous phase, Phase 7, had introduced per-partition dispatch — breaking proof generation into 10 partitions that could be processed independently. However, benchmarking revealed a critical bottleneck: a C++ static mutex in generate_groth16_proofs_c that locked the entire GPU operation, including CPU preprocessing steps that could otherwise run in parallel. This created GPU idle gaps where one worker would hold the mutex during CPU work while another worker sat idle waiting for GPU access.

Phase 8, implemented in the commit 2fac031f just before this sweep, solved this by narrowing the mutex scope. The C++ CUDA kernel was refactored to accept a passed-in mutex pointer, and the lock was reduced to cover only the CUDA kernel region (NTT+MSM, batch additions, tail MSMs). CPU preprocessing and the b_g2_msm operation now run outside the lock. This allows two GPU workers per device to interleave: while Worker A runs CUDA kernels, Worker B can perform CPU preprocessing, and vice versa. The result was a dramatic improvement in GPU efficiency — from visible idle gaps to 100.0% utilization in single-proof benchmarks — and a 13-17% throughput improvement over Phase 7.

Why This Message Was Written: The Sweep

The user's request was succinct: "sweep 10,12,15,18,20." This referred to the partition_workers configuration parameter, which controls how many partition synthesis tasks can run concurrently. The assistant had already tested partition_workers = 20 (the default) and partition_workers = 30 during Phase 8 validation. The pw=30 test had regressed badly to 60.4s/proof — 37% slower than pw=20's 44.0s/proof — because 30 simultaneous synthesis workers on a 96-core machine starved the GPU preprocessing threads of CPU resources.

The user wanted a finer-grained sweep between 10 and 20 to find the true optimal setting. The assistant's reasoning was straightforward: systematically benchmark each configuration under identical conditions (same machine, same C1 input file, same concurrency settings of c=5 and j=3), restarting the daemon between runs to ensure clean state. The methodology was empirical and disciplined: each pw value would get its own daemon process, its own log file, and a standardized 5-proof batch benchmark.

Assumptions and Input Knowledge

The sweep rested on several assumptions. First, that the benchmark is reproducible — that running the same 5-proof batch multiple times yields consistent results. The assistant implicitly assumed that the SRS preload time and CUDA kernel warmup effects are amortized across the batch, and that the c=5 j=3 setting (5 proofs total, 3 concurrent) provides sufficient statistical signal. Second, that the machine's 96 cores are the relevant resource constraint — the assistant had already established that pw=30 caused CPU contention, and the sweep was designed to find the boundary where contention begins. Third, that the daemon's configuration file is the correct mechanism for changing partition_workers — requiring a full restart rather than a hot-reload.

The input knowledge required to understand this message is substantial. One must know that partition_workers controls the number of concurrent synthesis threads; that synthesis is CPU-bound while the subsequent GPU operations are GPU-bound; that the Phase 8 dual-worker interlock allows two GPU workers to share a device; that the SRS preload is a one-time cost at daemon startup; and that the benchmark tool cuzk-bench sends proof requests to the daemon's HTTP API at 127.0.0.1:9820. Without this context, the message appears to be merely restarting a server — but it is actually a carefully controlled experiment in a complex optimization space.

Operational Challenges and Debugging

The message at index 2264 was not the first attempt at pw=12. In the preceding messages ([msg 2255] through [msg 2263]), the assistant encountered a series of operational failures that illustrate the fragility of automated benchmarking. The initial attempt used a sed command to modify the config file in-place, but this was bundled into a single bash call with pkill and nohup. When the sed substitution failed — because the config file still contained partition_workers = 10 from the previous write, and the sed pattern expected 10 but the file literally had 10 — the daemon started with the wrong configuration. A subsequent timeout caused the assistant to lose track of the daemon's state. The assistant had to debug by checking the config file contents, discovering that the sed hadn't taken effect, and then rewriting the entire config file from scratch using a heredoc.

This debugging sequence reveals an important aspect of the assistant's thinking process: it operates through trial and error within the constraints of the bash tool, where commands can timeout (120 seconds) and compound commands (pkill + sed + nohup in one call) can fail silently when earlier commands terminate the shell or consume the input. The assistant learned from each failure, eventually adopting a more robust pattern: kill the daemon in a separate call, verify the config file contents, write the config explicitly, then start the daemon in yet another call. This pattern is visible in the successful pw=12 launch at message 2264.

The Results and Output Knowledge

The sweep produced a clear empirical result. The assistant's subsequent messages (2266-2288) recorded the throughput for each configuration:

| partition_workers | Throughput (s/proof) | |---|---| | 10 | 43.5 | | 12 | 43.5 | | 15 | 44.8 | | 18 | 43.8 | | 20 | 44.9 |

The data reveals a narrow performance band with a clear optimum at pw=10–12 (43.5s/proof), a slight regression at pw=15 (44.8s), a recovery at pw=18 (43.8s), and a further regression at pw=20 (44.9s). The assistant's earlier pw=20 benchmark had shown 44.0s/proof, suggesting some run-to-run variability of about 1 second. The key insight is that the optimal range is 10–12, not the default of 20. This makes intuitive sense: with 10–12 partition workers on a 96-core machine, each worker gets approximately 8–9 cores, leaving enough headroom for GPU preprocessing threads. At pw=20, each worker gets only 4–5 cores, and the contention begins to hurt.

The output knowledge created by this message and its successors is a production-ready configuration recommendation: partition_workers = 10 or 12 for this specific hardware (96-core Zen4, RTX 5070 Ti). More broadly, it establishes a methodology for tuning this parameter on any machine: sweep across candidate values, measure throughput with a standardized benchmark, and identify the point where CPU contention begins to degrade performance.

The Thinking Process

The assistant's reasoning, visible across the sweep, follows a systematic experimental pattern. It maintains a todo list tracking each sweep point's status. It uses consistent benchmarking conditions (c=5, j=3) across all runs. It isolates variables by restarting the daemon for each configuration. When operations fail, it diagnoses the root cause — the sed not persisting, the compound command being truncated — and adapts its approach. The thinking is not explicitly shown in the message itself (which is purely a bash command), but the surrounding messages reveal a disciplined experimental mindset: measure, record, compare, and iterate.

Conclusion

The message at index 2264 is a single bash command in a larger experimental sweep, but it encapsulates the essence of performance engineering: systematic measurement under controlled conditions. It was written because the assistant needed to restart the proving daemon with a new partition_workers value as part of a five-point sweep requested by the user. The sweep succeeded in identifying the optimal configuration (pw=10–12), producing actionable knowledge for production deployment. The operational hiccums along the way — failed sed substitutions, command timeouts, lost daemon processes — are not bugs but features of a realistic engineering workflow, where the assistant must debug its own tooling as it goes. In the end, the sweep validated that Phase 8's dual-worker GPU interlock delivers its best throughput with a modest 10–12 concurrent partition workers, completing a chapter in the ongoing optimization of Filecoin's proof generation pipeline.