The Quiet Benchmark: How One Bash Command Revealed the Limits of Synthesis Parallelism

The Message

[bash] grep "effective_lookahead" /home/theuser/cuzk-p12-nodebug-pw16.log; nohup bash -c 'while true; do ps -o rss= -p $(pgrep -f cuzk-daemon | head -1) 2>/dev/null | awk "{printf \"%s RSS: %.1f GiB\n\", strftime(\"%H:%M:%S\"), \$1/1048576}"; sleep 5; done' > /tmp/rss-nodebug-pw16.log 2>&1 & echo "RSS=$!"

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[2026-02-20T14:33:50.277169Z INFO cuzk_core::engine] starting pipeline: synthesis task + GPU workers configured_lookahead=1 partition_workers=16 effective_lookahead=16 num_gpus=2

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RSS=1189868

At first glance, this message from an opencode coding session appears to be a routine operational command — a developer checking a configuration value and starting a memory monitoring script before running a benchmark. But in the context of a months-long optimization campaign targeting Filecoin's Groth16 proof generation pipeline, this single message represents a pivotal moment: the culmination of a memory backpressure redesign that transformed an OOM-prone system into one capable of safely exploring the outer bounds of its parallelism.

The Optimization Journey

To understand why this message matters, one must understand the journey that led to it. The assistant and user had been engaged in a deep optimization effort across multiple phases (Phase 9 through Phase 12) of the cuzk SNARK proving engine, the component responsible for generating Filecoin Proof-of-Replication (PoRep) proofs. The pipeline involves synthesizing circuit partitions on the CPU, then shipping them to GPUs for the heavy number-theoretic transform (NTT) and multi-scalar multiplication (MSM) computations.

The critical bottleneck was memory. Each synthesized partition consumed roughly 12 GiB of evaluation vectors (the a/b/c wires of the Groth16 prover), and when synthesis outpaced GPU consumption — which it invariably did — completed partitions would pile up in memory. With 10–16 partitions per proof and multiple proofs in flight, the system would routinely exhaust the 755 GiB memory budget and OOM (out-of-memory) kill the daemon. The Phase 12 split API redesign had decoupled the GPU proving path from CPU post-processing, but it introduced a new problem: the synthesis→GPU channel had a hardcoded capacity of 1, creating a bottleneck that both limited throughput and failed to bound memory.

The breakthrough came in the form of three coordinated changes: early deallocation of a/b/c evaluation vectors immediately after GPU submission (freeing ~12 GiB per partition), auto-scaling the channel capacity to match the number of partition workers, and holding the semaphore permit through the channel send rather than releasing it at synthesis completion. Together, these changes transformed the memory profile. Where partition_workers=12 had previously OOM'd at 668 GiB peak RSS, it now ran comfortably at 383 GiB — a 40% reduction.

Why This Message Was Written

This message sits at the boundary between validation and exploration. Having proven that the memory backpressure fix worked for pw=12 (37.7s/proof, 383 GiB RSS) and pw=14 (37.8s/proof, 456 GiB RSS), the assistant is now probing the upper limits of the design. The question driving this message: can more synthesis parallelism improve throughput, or have we hit a different bottleneck?

The assistant's reasoning is visible in the sequence of benchmarks leading up to this point. Each increment in partition_workers (pw) was tested methodically: pw=10, pw=12, pw=14, and now pw=16. The pattern in the data was already suggestive. pw=10 delivered 38.5s/proof. pw=12 improved to 37.7s/proof — a meaningful 2% gain. pw=14 regressed slightly to 37.8s/proof. The marginal returns were diminishing, and the memory cost was rising: 317 GiB, 399 GiB, 456 GiB respectively. The assistant suspects that the system is approaching the DDR5 memory bandwidth wall — the point where additional CPU-side synthesis parallelism merely increases contention for the same memory bus, yielding no throughput benefit while consuming more memory.

This message is the setup for the test that will confirm or refute that hypothesis. The assistant needs to know two things: whether the configuration was applied correctly (the effective_lookahead check) and what the memory consumption looks like during the run (the RSS monitor).

Technical Anatomy of the Commands

The message contains two commands fused into a single bash invocation, separated by a semicolon. The first command is diagnostic:

grep "effective_lookahead" /home/theuser/cuzk-p12-nodebug-pw16.log

This searches the daemon's startup log for the line logged by cuzk_core::engine when the pipeline initializes. The log line reveals four critical parameters: configured_lookahead=1 (the base synthesis lookahead, a legacy parameter now largely superseded by the auto-scaling logic), partition_workers=16 (the number of CPU threads synthesizing circuit partitions), effective_lookahead=16 (the actual channel capacity after auto-scaling, computed as max(configured_lookahead, partition_workers)), and num_gpus=2 (the number of GPU workers consuming partitions). The equality of partition_workers and effective_lookahead confirms that the auto-scaling logic is working correctly — the channel can now hold all 16 in-flight partitions, preventing the send() blocking that previously caused memory pileups.

The second command starts a background RSS monitoring loop:

nohup bash -c 'while true; do ps -o rss= -p $(pgrep -f cuzk-daemon | head -1) 2>/dev/null | awk "{printf \"%s RSS: %.1f GiB\n\", strftime(\"%H:%M:%S\"), \$1/1048576}"; sleep 5; done' > /tmp/rss-nodebug-pw16.log 2>&1 &

This is a pattern the assistant has used throughout the optimization campaign. Every 5 seconds, it polls the daemon's RSS (resident set size) via ps, converts bytes to gibibytes, timestamps the reading, and appends it to a log file. The nohup and background (&) ensure the monitor survives the shell session. The 2>&1 redirects stderr to the same log. The output RSS=1189868 confirms the monitor process started with PID 1189868.

The Significance of effective_lookahead=16

The log line effective_lookahead=16 is the quiet triumph of the Phase 12 memory backpressure work. In the original design, the channel capacity was hardcoded to 1, meaning only one partition could be in transit from synthesis to GPU at any time. If the GPU was busy, the synthesis thread would block on send(), holding its 12 GiB partition in memory while waiting. With multiple synthesis threads, this created a traffic jam: threads would complete synthesis, find the channel full, and sit blocked with their partitions alive, while the GPU slowly consumed one at a time.

The auto-scaling fix changed the channel capacity from 1 to max(synthesis_lookahead, partition_workers). With pw=16, the effective lookahead is 16, meaning the channel has slots for all 16 partitions simultaneously. A synthesis thread can send() its partition immediately and move on to the next task, releasing its working memory. The semaphore permit — which bounds the total number of partitions in the entire system (synthesis + channel + GPU) — is released only after the send succeeds, ensuring the system-wide limit is respected. The result is a smooth, non-blocking pipeline where synthesis and GPU work are decoupled by the channel's buffering capacity, not by a hardcoded bottleneck.

Assumptions and the DDR5 Wall

The assistant is operating under a clear hypothesis: that DDR5 memory bandwidth, not synthesis throughput, is the limiting factor. This assumption is grounded in the data. As pw increased from 10 to 12 to 14, throughput plateaued at ~37.7-38.5s/proof while memory consumption rose from 317 GiB to 456 GiB. The pattern suggests that additional synthesis threads are spending more time waiting for memory access than doing useful work, a classic symptom of bandwidth saturation on a multi-socket server with multiple memory channels.

The assistant also assumes that the GPU is not the bottleneck. With num_gpus=2 and gpu_threads=32, the GPU workers are processing partitions at a mean of ~7.3s per partition (from the GPU timing data in earlier messages). With 10 partitions per proof and 2 GPUs, the GPU throughput is roughly 20 / (7.3 * 10 / 2) ≈ 0.55 proofs/second, or ~36.4s/proof — close to the observed 37.7s. The slight gap suggests the CPU side (synthesis + memory transfer) is adding ~1.3s of overhead, which the assistant attributes to memory bandwidth contention.

If this assumption is correct, pw=16 will show no further throughput improvement and will simply consume more memory. If it's incorrect — if synthesis throughput is still the bottleneck — pw=16 might squeeze out another 1-2% gain. The assistant is letting the data decide.

The Methodology of Systematic Benchmarking

This message exemplifies a rigorous benchmarking methodology that deserves attention. The assistant is not making ad-hoc changes and hoping for improvement. Each parameter is varied independently while holding others constant (gw=2, gt=32 throughout). Each configuration is benchmarked with a consistent workload (20 proofs, concurrency 20). Memory is tracked continuously via the RSS monitor, not just sampled at the end. The daemon is restarted between configurations to avoid memory fragmentation artifacts from previous runs. Multiple runs are performed to distinguish systematic effects from noise (pw=12 got two runs: 37.7s and 38.5s, yielding an average of ~38.1s).

The assistant also pays attention to operational details that could confound results: port binding issues from a previous daemon not fully shutting down (visible in the pw=16 startup sequence where the daemon failed to start initially), the need to wait for the daemon to be "ready" before benchmarking, and the conversion of debug eprintln! calls to tracing::debug! to eliminate I/O noise from the benchmark measurements.

Conclusion

This single message — a bash command checking a configuration value and starting a memory monitor — is the quiet prelude to a decisive experiment. It represents the point where the months-long memory backpressure work has made the system stable enough to probe its outer limits. The assistant is not fighting fires anymore; it is methodically characterizing the performance envelope. Whether pw=16 yields a breakthrough or confirms the DDR5 bandwidth wall, the answer will inform the next phase of optimization — perhaps a move toward Phase 13's planned interventions for reducing memory bandwidth contention.

In the broader narrative of the optimization campaign, this message is the calm before the data arrives. The assistant has built the machine, fixed the leaks, tuned the parameters, and is now asking the final question: how fast can this pipeline actually go?