A Moment of Debugging: How a Shell Scripting Bug Revealed the Baseline Memory Footprint of a Groth16 Proof Engine

In the midst of an intensive optimization campaign targeting Filecoin's SUPRASEAL_C2 Groth16 proof generation pipeline, a single assistant message stands out not for its complexity, but for what it reveals about the nature of systems engineering. Message [msg 3287] is a brief, almost mundane debugging moment: the assistant realizes a shell command has gone wrong, fixes it, and extracts a crucial piece of data. Yet this moment encapsulates the iterative, error-prone process of characterizing real-world system behavior, and the numbers it produces carry significant weight for the entire optimization effort.

The Context: A Systematic Low-Memory Benchmark Sweep

The message arrives during Segment 32 of a long-running investigation into the memory and throughput characteristics of the cuzk engine — a custom Groth16 prover for Filecoin's Proof-of-Replication (PoRep) circuits. The project had just completed Phase 12, a major architectural overhaul that introduced a split GPU proving API with memory backpressure mechanisms, achieving a throughput of ~37.7 seconds per proof at 400 GiB peak memory with 12 partition workers. But these numbers were for a high-memory configuration. The user's request in [msg 3272] was to explore the other end of the spectrum: "Run cuzk with lower parallelsms to see how low we can get RSS requirements on smaller systems and the timings."

This was a practical, deployment-oriented question. Not every operator has 768 GiB of RAM. The goal was to produce a data-driven configuration guide showing what throughput one could expect on systems with 128 GiB, 256 GiB, or 512 GiB of memory. The assistant responded by planning a sweep across partition worker counts of 1, 2, 5, and 7, with gpu_workers_per_device set to 1 (to minimize GPU-side in-flight memory), creating dedicated config files for each combination ([msg 3276]).

The Benchmark Run and the First Error

The first run targeted pw=1 gw=1 — the absolute minimum parallelism. With only one partition worker, the engine would synthesize partitions sequentially rather than in parallel. The benchmark completed, but the results were sobering: each proof took roughly 292 seconds of wall-clock time, because the 10 partitions of the PoRep circuit were being processed one after another, each taking ~29 seconds. The per-proof "prove" time was a respectable ~33 seconds, but the queueing delay from sequential synthesis dominated.

More critically, the memory monitoring attempt failed. The assistant had launched a background subshell to poll /proc/$DAEMON_PID/status every 2 seconds, but the RSS log file was empty ([msg 3285]). The background process had likely been killed when the benchmark's timeout or the pkill command in a subsequent step terminated it. This left the assistant without the very data the benchmark was designed to collect.

The Mistake: When pgrep Returns Too Much

In [msg 3286], the assistant tried to recover by querying the daemon's RSS directly:

DAEMON_PID=$(pgrep -f "cuzk-daemon --config /tmp/cuzk-lowmem-pw1-gw1.toml")

The problem was subtle but classic. The pgrep -f pattern matched not only the daemon process but also the grep command that the assistant was running in the same pipeline — because the grep process itself had the string "cuzk-daemon --config /tmp/cuzk-lowmem-pw1-gw1.toml" in its command line. pgrep returned two PIDs: the daemon's PID and the grep's PID. When assigned to a shell variable, these two numbers were concatenated (with a newline) into a single string like 1449837\n1556731. When this corrupted string was used in the path /proc/$DAEMON_PID/status, the shell expanded it to /proc/1449837\n1556731/status, which does not exist. The error message was clear: "No such file or directory."

This is a classic shell scripting pitfall. pgrep -f is powerful but dangerous — it matches against the full command line of every running process, including the pgrep command itself and any shell pipelines that contain the pattern string. The fix, as the assistant recognized, was to either use a more specific pattern or to take only the first result with head -1.

The Fix and the Revelation

Message [msg 3287] is the correction:

Multiple PIDs were returned. Let me fix the grep:

>

``bash DAEMON_PID=$(pgrep -f "cuzk-daemon --config" | head -1) echo "Daemon PID: $DAEMON_PID" if [ -n "$DAEMON_PID" ]; then grep -E "VmRSS|VmHWM" /proc/$DAEMON_PID/status fi ``

>

Daemon PID: 1449837 VmHWM: 108845152 kB VmRSS: 77207076 kB

The assistant made two key changes. First, it shortened the pgrep pattern to "cuzk-daemon --config" — enough to uniquely identify the daemon without including the full config path that might appear in other processes. Second, it piped through head -1 to take only the first matching PID. This is a pragmatic but imperfect fix: if multiple daemon instances were running, head -1 would silently pick one. In this context, with a single daemon, it worked correctly.

The output was immediately valuable. The daemon's peak memory (VmHWM) was 108,845,152 kB — approximately 103.8 GiB. Its current RSS was 77,207,076 kB — approximately 73.6 GiB. These numbers represent the engine's baseline memory footprint with minimal parallelism: one partition worker and one GPU worker.

What the Numbers Mean

The 104 GiB peak with pw=1 gw=1 is a significant finding. It reveals that even when the engine is configured for minimal parallelism, there is a substantial fixed memory cost. This baseline includes:

The Broader Significance

This message is a small but critical moment in the larger narrative of systems optimization. It demonstrates several important principles:

First, measurement is hard. Even a seemingly simple task — read a process's RSS from /proc — can fail in unexpected ways when shell scripting edge cases collide with the messy reality of running processes. The assistant's RSS monitor script failed silently; the direct query returned a corrupted path. Each failure required diagnosis and a corrected approach.

Second, baseline characterization matters. Before the Phase 12 optimizations, the engine's peak memory was ~200 GiB. The optimizations brought it down, but the question remained: how low can it go? The pw=1 gw=1 measurement establishes the floor — the irreducible memory cost of the engine's architecture. Any future optimization that claims to reduce memory further must beat this baseline.

Third, debugging is iterative. The assistant didn't get the memory data on the first try, or the second. Each attempt revealed a new problem: the monitor log was empty, the PID variable was corrupted, the grep pattern was too broad. Message [msg 3287] is the third attempt, and it finally succeeds. This pattern of trial, error, diagnosis, and correction is the rhythm of real systems work.

Conclusion

Message [msg 3287] is, on its surface, a simple shell command fix. But in the context of the broader optimization effort, it represents a critical juncture: the moment when the assistant successfully extracted the baseline memory footprint that would anchor the entire low-memory configuration guide. The 104 GiB peak at pw=1 gw=1 is not just a number — it is a constraint that shapes all subsequent deployment recommendations, a data point that validates the memory model, and a reminder that even the most carefully planned benchmarks can be derailed by a single pgrep returning two lines instead of one.