The Second Measurement: Confirming a Synthesis Breakthrough with perf stat

In the middle of a multi-week performance optimization campaign for Filecoin's Groth16 proof generation pipeline, a single bash command represents the disciplined engineering rigor that separates a lucky coincidence from a validated improvement. The message at <msg id=1210> is deceptively simple: a perf stat invocation running a synthesis-only microbenchmark for the second time, capturing the synthesis time of 51.12 seconds for a 32 GiB PoRep C2 partition. But this message is the culmination of a chain of reasoning that began with a perf record profile showing that Boolean::lc() — a method that creates a fresh LinearCombination allocation on every call — accounted for 6.51% of synthesis time, and that temporary LC constructions in total consumed 23.52% of the ~55-second CPU synthesis phase. The assistant had just implemented Boolean::add_to_lc() and Boolean::sub_from_lc() methods across six files in three separate crate forks (bellpepper-core, bellperson, and supraseal-c2), patching hot call sites in UInt32::addmany, Num::add_bool_with_coeff, Boolean::enforce_equal, Boolean::sha256_ch, Boolean::sha256_maj, and two lookup table gadgets. The first microbenchmark run showed 50.9 seconds average over three iterations. Now the assistant is collecting hardware counter evidence to understand why.

The Motivation: Proving the Optimization Works, and Why

The perf stat command in this message is not the first measurement — it is the second. Message <msg id=1209> already ran the same command, capturing a synthesis time of 51.22 seconds and writing counters to /tmp/perf-add-to-lc-run1.txt. Running a second measurement serves multiple purposes. First, it establishes reproducibility: a single data point could be contaminated by thermal throttling, background processes, or kernel scheduling noise. Two consistent readings (51.22s and 51.12s) provide confidence that the ~8% improvement over the 55.4-second baseline is real. Second, the hardware counters collected by perf stat — cycles, instructions, cache misses, branch predictions — tell the mechanism of the improvement, not just its magnitude. The assistant is building an A/B comparison dataset that will later reveal that the optimization eliminated 91 billion instructions (a 15.3% reduction) and 18.6 billion branches (a 26.7% reduction), confirming that the primary benefit came from removing allocation and branch logic, not from cache effects.

The choice of perf stat events is itself revealing. The assistant selected L1-dcache-loads, L1-dcache-load-misses, LLC-loads, and LLC-load-misses alongside the standard cycles, instructions, and branches. This reflects a sophisticated understanding of the Zen4 microarchitecture: earlier in Phase 4, the assistant had tested a SmallVec optimization that reduced cache misses but hurt IPC (instructions per cycle) from 2.60 to 2.38, proving that on AMD's Zen4 out-of-order engine, a simpler instruction stream with more cache misses can outperform a complex one with fewer cache misses. The Boolean::add_to_lc optimization is expected to reduce both instructions and cache misses by eliminating the allocation, initialization, and deallocation of temporary LinearCombination objects — and the perf counters will confirm whether this holds.

The Context of the Measurement

To understand why this message exists, one must understand the performance landscape the assistant was navigating. The Phase 4 optimization campaign had already suffered two reversals. The SmallVec optimization (A1) was tested in three configurations (capacities of 1, 2, and 4 elements) and all were slower than plain Vec — the enum discriminant checks and larger stack frames defeated Zen4's out-of-order engine. The cudaHostRegister optimization (B1) was tested and found to add 5.7 seconds of overhead from mlock syscalls touching every page of 125 GB of host memory. A third attempt at interleaved A+B evaluation was reverted after it hurt IPC. The team was running out of easy wins.

The breakthrough came from perf record profiling, which revealed that 23.52% of synthesis time was spent constructing LinearCombination objects — specifically, the Boolean::lc() method that creates a fresh LinearCombination::zero() (triggering a Vec allocation) on every call, even when wrapping only 1-2 terms. In tight loops like UInt32::addmany, Boolean::lc() is called 32 times per operand. The fix was conceptually simple: add Boolean::add_to_lc() and Boolean::sub_from_lc() methods that add or subtract a boolean's contribution directly to an existing LinearCombination, bypassing the temporary allocation entirely. But implementing this required patching every call site across three crate forks — a surgical modification of the gadget layer.

The first microbenchmark (msg 1207) ran three iterations and averaged 50.9 seconds, down from 55.4 seconds. The first perf stat run (msg 1209) confirmed 51.22 seconds. Now, in this message, the assistant runs a second perf stat measurement, capturing 51.12 seconds. The consistency between the two runs — within 0.1 seconds — confirms that the improvement is stable and that the optimization does not introduce variance or instability.

What the Message Reveals About the Engineering Process

This message is a window into a disciplined, measurement-driven optimization methodology. The assistant does not simply check "does it compile?" and "does it produce a correct proof?" — it asks "how much faster?" and "why?" at every step. The perf stat tool is used not as an afterthought but as a primary instrument, collecting hardware-level evidence that can be compared against baseline runs saved in /tmp/perf-vec-run1.txt and /tmp/perf-vec-run2.txt. The naming convention — /tmp/perf-add-to-lc-run2.txt — shows that the assistant is maintaining a structured log of measurements, each labeled by optimization name and run number.

The command itself reveals several design decisions. The -i 1 flag runs only a single iteration, because perf stat aggregates counters over the entire process lifetime and multiple iterations would blur the measurement. The --partition 0 flag selects a single partition of the 32 GiB PoRep C2 proof, which is sufficient for a representative microbenchmark. The FIL_PROOFS_PARAMETER_CACHE environment variable points to /data/zk/params, the standard parameter cache location. The 2>&1 | tee pattern captures both the synthesis time log output and the perf counters to a file for later analysis.

The synthesis time of 51.12 seconds, when combined with the earlier 51.22-second measurement, gives the assistant confidence to proceed to the next step: a full end-to-end proof. But as the chunk summary reveals, that E2E test will uncover a new problem — a GPU wrapper regression where the bellperson wrapper time increased from 34.0s to 36.0s despite identical CUDA internal timing. This will lead to the discovery of synchronous destructor overhead from freeing ~37 GB of C++ vectors and ~130 GB of Rust Vecs, which will be fixed with async deallocation, ultimately bringing the total E2E time to 77.2 seconds — a 13.2% improvement over the 88.9-second baseline.

The Deeper Significance: Measurement Culture in Performance Engineering

What makes this message noteworthy is not the 51.12-second number itself, but what it represents: the moment when a hypothesis — "temporary LC allocations are a significant bottleneck" — is confirmed by two independent measurements with hardware counter evidence. The assistant could have declared victory after the first microbenchmark showed 50.9 seconds. Instead, it ran a second measurement with perf stat to collect counters, and then a third (this message) to confirm reproducibility. This is the scientific method applied to software optimization: form a hypothesis from profiling data, implement a targeted fix, measure the effect, and verify with multiple samples.

The message also illustrates the layered nature of performance work in a complex system like Groth16 proving. The synthesis phase is CPU-bound, running on a 96-core AMD Threadripper PRO 7995WX. The GPU phase runs on an RTX 5070 Ti. Optimizations at one layer can have unexpected effects at another — as the assistant will soon discover when the synthesis improvement reveals a previously hidden GPU wrapper regression. The Boolean::add_to_lc optimization is a pure CPU win, but its measurement must be isolated from GPU effects, which is why the assistant uses the synth-only subcommand of cuzk-bench (feature-gated behind synth-bench) to measure synthesis independently.

Input Knowledge Required

To fully understand this message, one must understand several layers of context. At the application level, one needs to know that Filecoin's Proof-of-Replication (PoRep) uses Groth16 proofs over the BLS12-381 curve, and that a 32 GiB sector requires synthesizing a circuit with millions of constraints across 10 parallel partitions. At the data structure level, one must understand that LinearCombination is the core representation of constraint system terms in bellpepper-core, and that Boolean::lc() converts a boolean variable into a linear combination by allocating a new Vec. At the tooling level, one must know that perf stat is a Linux profiling tool that reads hardware performance counters from the CPU's Performance Monitoring Unit (PMU), and that the Zen4 architecture has specific characteristics around cache hierarchy and out-of-order execution that make instruction count and branch prediction critical metrics. At the project level, one must understand the three-crate fork structure (bellpepper-core, bellperson, supraseal-c2) and the [patch.crates-io] mechanism in Cargo that allows local modifications to upstream dependencies.

Output Knowledge Created

This message creates several forms of knowledge. The immediate output is a second data point (51.12s) and a set of hardware counters saved to /tmp/perf-add-to-lc-run2.txt. But the broader output is the confirmation that the Boolean::add_to_lc optimization is robust and reproducible, which justifies proceeding to the more expensive E2E test. The hardware counters, when compared against the Vec baseline, will quantify the improvement in terms of instructions retired, branches predicted, and cache behavior — providing a mechanistic explanation that can inform future optimization work. The message also contributes to the project's measurement archive, creating a chain of evidence that will be referenced when the Phase 4 changes are committed as 2da2a901 and when the results are documented in the project plan.

Conclusion

A single perf stat command, capturing 51.12 seconds of synthesis time, might seem like a minor entry in a long optimization campaign. But it represents the disciplined practice of measurement-driven engineering: the refusal to accept a single data point, the commitment to collecting hardware-level evidence, and the understanding that performance optimization is a scientific process of hypothesis, experiment, and verification. The Boolean::add_to_lc optimization that this message validates would go on to be part of a 13.2% end-to-end improvement, but only because the assistant took the time to measure it twice.