The Build That Confirmed a Hypothesis: Diagnosing a SmallVec Regression on AMD Zen4

Introduction

In the high-stakes world of Filecoin proof generation, every second counts. When the cuzk team implemented Phase 4 optimizations for their Groth16 proving pipeline, they expected improvements — instead, they got a 17-second regression. What followed was a masterclass in disciplined performance engineering: systematic reversion of suspected changes, precise CUDA timing instrumentation, microbenchmark construction, and ultimately, a deep dive into CPU cache architecture. At the center of this investigation sits a single, seemingly mundane build command — message <msg id=996> — whose output of nine compilation lines represents the culmination of a diagnostic chain that would reveal why an optimization intended to eliminate heap allocations was paradoxically making synthesis 10% slower.

The Subject Message

The message itself is brief and unremarkable on its surface:

[assistant] [bash] cargo build --release -p cuzk-daemon 2>&1 | tail -10
   Compiling storage-proofs-core v19.0.1
   Compiling storage-proofs-porep v19.0.1
   Compiling storage-proofs-post v19.0.1
   Compiling storage-proofs-update v19.0.1
   Compiling filecoin-proofs v19.0.1
   Compiling filecoin-proofs-api v19.0.0
   Compiling cuzk-core v0.1.0 (/home/theuser/curio/extern/cuzk/cuzk-core)
   Compiling cuzk-server v0.1.0 (/home/theuser/curio/extern/cuzk/cuzk-server)
   Compiling cuzk-daemon v0.1.0 (/home/theuser/curio/extern/cuzk/cuzk-daemon)
    Finished `release` pr...

A successful build. Nine packages recompiled, culminating in cuzk-daemon. The Finished line confirms the binary is ready. But to understand why this build matters, we must trace the reasoning that led to it — a chain of performance diagnosis that spans dozens of messages and multiple reverts, microbenchmarks, and hardware-level analysis.

The Context: A Regression Unfolds

The story begins with Phase 4 of the cuzk project, which aimed to apply five optimizations to the already-optimized pipelined Groth16 proving engine. The baseline was an impressive 88.9 seconds for a single 32 GiB PoRep proof. The five optimizations were:

• A1 (SmallVec): Replace Vec with SmallVec in the Indexer data structure used during constraint synthesis, to eliminate heap allocations for small linear combinations
• A2 (Pre-sizing): Pre-allocate vectors with known capacities to avoid reallocation
• A4 (Parallel B_G2): Parallelize the B_G2 MSM (Multi-Scalar Multiplication) on CPU
• B1 (cudaHostRegister): Pin host memory for a/b/c vectors to accelerate GPU transfers
• D4 (Per-MSM window tuning): Tune MSM window sizes for the specific proof parameters When applied together, the result was not an improvement but a regression to 106 seconds — a 17-second slowdown. The assistant's response was methodical: revert suspected changes one by one, measure the impact, and isolate the culprit.

The Diagnostic Trail

The first suspect was B1 (cudaHostRegister). The assistant had already added CUDA timing instrumentation (CUZK_TIMING printf's) to the GPU code, but discovered that the printf output was being lost due to buffering when stdout was redirected. After adding fflush(stderr) calls, the first timing breakdown was collected. It showed that B1 was adding 5.7 seconds of overhead by pinning ~125 GiB of host memory — far exceeding the estimated 150–300 ms. Reverting B1 brought the total down to 94.4 seconds.

But the regression wasn't fully resolved. Synthesis was still at 60.3 seconds versus the 54.7-second baseline — a 5.6-second gap. The only remaining synthesis change was A1 (SmallVec).

To isolate the synthesis slowdown without the noise of GPU proving and SRS loading, the assistant built a synth-only microbenchmark subcommand in cuzk-bench. This enabled rapid A/B testing of the SmallVec change. Four configurations were benchmarked (three iterations each):

• Vec (original): 54.5 seconds
• SmallVec cap=1: 59.6 seconds
• SmallVec cap=2: 60.0 seconds
• SmallVec cap=4: 60.2 seconds The results were conclusive: SmallVec, regardless of inline capacity, caused a ~5–6 second regression in synthesis time. This was deeply counterintuitive — SmallVec was supposed to eliminate heap allocations, which should be faster, not slower.

The Cache Line Hypothesis

The user's input — "Optimize for AMD Zen3+" — reframed the investigation. The system runs on an AMD Zen4 Threadripper PRO 7995WX, with specific cache characteristics:

• L1d: 32 KB per core, 8-way, 64-byte cache lines
• L2: 1 MB per core (Zen4)
• L3: Shared per CCD, up to 32 MB per 8-core CCD The assistant's analysis in message <msg id=995> revealed the key insight. With INDEXER_INLINE_CAP = 4, each Indexer struct was ~170 bytes (4 × 40 bytes for (usize, Scalar) entries + metadata). During enforce(), three LinearCombination objects are created, each containing two Indexer instances — that's 6 Indexers per call, totaling ~1020 bytes of inline stack data spread across 16 cache lines. In the tight inner loop of constraint synthesis, this extra stack pressure was causing L1d cache evictions and slowing down the entire pipeline. With INDEXER_INLINE_CAP = 1, each Indexer would be ~56 bytes, and the set of 6 would fit in ~5 cache lines — much better L1d residency. The assistant also noted that Zen3+ has excellent branch prediction and prefetching, and that jemalloc's thread-local cache on this architecture is very fast (~10-15ns per allocation), meaning the Vec path's pointer chase to heap data would likely hit L2 (1 MB) since the thread-local arena remains hot. This directly contradicted the original assumption in the optimization proposal that heap allocations were a significant bottleneck.

What This Build Represents

Message <msg id=996> is the build that compiles the INDEXER_INLINE_CAP = 1 change into the full daemon binary. The build output shows the dependency chain: bellpepper-core (where the SmallVec change lives) is not directly listed, but its downstream dependents are: storage-proofs-core, storage-proofs-porep, storage-proofs-post, storage-proofs-update, filecoin-proofs, filecoin-proofs-api, cuzk-core, cuzk-server, and finally cuzk-daemon. Each of these packages had to be recompiled because the type change in Indexer propagates through the entire constraint system.

The Finished line confirms that the build succeeded — the next step would be to run the benchmark and see if cap=1 fixes the regression. This build is the gateway to the critical experiment that would either validate or refute the cache line hypothesis.

Decisions Made

Several decisions are crystallized in this message:

1. Pursue the cache line hypothesis: Rather than reverting A1 entirely (which would abandon the optimization), the assistant chose to test a smaller inline capacity. This was a targeted experiment, not a wholesale revert.
2. One-character change: The edit was minimal — changing INDEXER_INLINE_CAP from 4 to 1. This reflects a scientific approach: isolate one variable, measure its effect.
3. Full rebuild: Rather than running a synth-only microbenchmark (which tests synthesis in isolation), the assistant rebuilt the full daemon. This would enable an end-to-end test that captures any interactions between the SmallVec change and the rest of the pipeline.
4. Kill and restart: The daemon was killed before rebuilding, ensuring a clean state for the next test run.

Assumptions Made

The investigation rests on several assumptions:

1. SmallVec is the sole cause of the synthesis regression: This was supported by the microbenchmark data showing Vec at 54.5s and all SmallVec variants at ~60s, but it assumes no interaction effects with other Phase 4 changes that were still in place (A4 Parallel B_G2 and D4 Per-MSM window tuning).
2. Cache line alignment is the dominant factor: The hypothesis that stack frame size and L1d cache pressure explain the regression assumes that other factors (e.g., SmallVec's internal branching logic, discriminant checks, or alignment padding) are secondary.
3. Zen4 cache behavior is representative: The analysis used Zen4's specific cache parameters (32 KB L1d, 64-byte lines, 1 MB L2). If the actual behavior differs due to prefetching, out-of-order execution, or microarchitectural details, the hypothesis might not hold.
4. The build system correctly propagates changes: The assistant assumed that changing bellpepper-core/src/lc.rs would trigger recompilation of all downstream packages. The build output confirms this — nine packages were recompiled.

Potential Mistakes

The most significant potential mistake is not reverting A1 entirely first to establish a clean baseline with only A4 and D4 active. The microbenchmark had already shown that SmallVec causes a 5-6s regression regardless of capacity, so testing cap=1 is an optimization of a known-regressing change rather than a root-cause investigation. If cap=1 also regresses (which the microbenchmark data suggests it might — cap=1 was 59.6s vs Vec's 54.5s), the assistant will need to revert A1 entirely and accept that SmallVec is not beneficial on this architecture.

Another subtle issue: the assistant's analysis in <msg id=995> calculated Indexer sizes but may have underestimated the SmallVec metadata overhead. SmallVec<[(usize, T); N]> includes a discriminant byte, a length field (8 bytes), and potentially alignment padding. The actual struct size might be larger than the naive calculation of N × 40 + 9.

Input Knowledge Required

To fully understand this message, one needs:

1. The cuzk project architecture: Understanding that cuzk-daemon is the binary that runs the proving pipeline, and that it depends on cuzk-core, cuzk-server, and transitively on bellpepper-core (where the SmallVec change lives).
2. The Phase 4 optimization suite: Knowing which five optimizations were implemented and which have been reverted (A2, B1) versus still active (A1, A4, D4).
3. AMD Zen4 cache architecture: The specific parameters of L1d (32 KB, 64-byte lines), L2 (1 MB), and L3 (shared per CCD) are essential to the cache line hypothesis.
4. SmallVec semantics: Understanding that SmallVec stores up to N elements inline before spilling to heap, and that the inline storage increases the struct's stack footprint.
5. The Groth16 proving pipeline: Knowledge that enforce() is the core constraint synthesis function called millions of times, and that it creates LinearCombination objects with Indexer fields.

Output Knowledge Created

This message creates:

1. A testable binary: The rebuilt cuzk-daemon with INDEXER_INLINE_CAP = 1 is ready for benchmarking.
2. A confirmed build chain: The output proves that the SmallVec change successfully propagates through the entire dependency tree from bellpepper-core to cuzk-daemon.
3. A experimental state: The system is now in a state where the cache line hypothesis can be tested — run a single proof, measure synthesis time, compare to the Vec baseline and the cap=4 result.

The Thinking Process

The reasoning visible in the surrounding messages reveals a sophisticated diagnostic process:

1. Measure, don't guess: The assistant didn't assume which optimization caused the regression — it added CUDA timing instrumentation, collected phase-level breakdowns, and identified B1 as the primary culprit through data.
2. Isolate with microbenchmarks: When the synthesis regression remained after reverting B1, the assistant built a synth-only microbenchmark to test SmallVec in isolation, eliminating GPU and SRS loading noise.
3. Consider the target architecture: The user's hint about AMD Zen3+ triggered a deep analysis of cache characteristics, leading to the cache line hypothesis.
4. Formulate a testable prediction: The hypothesis predicts that cap=1 will reduce stack pressure and improve synthesis time compared to cap=4.
5. Execute the experiment: Message <msg id=996> is the execution step — build the change, then benchmark. This is textbook performance engineering: form a hypothesis, design a minimal experiment, execute, measure, and iterate.

Conclusion

Message <msg id=996> appears to be nothing more than a build log — nine lines of compilation output. But in context, it represents a pivotal moment in a rigorous performance diagnosis. The assistant had traced a 17-second regression through two reverted optimizations (B1 and A2), isolated the remaining suspect (A1 SmallVec), formulated a cache-level hypothesis based on AMD Zen4 architecture, and executed a targeted experiment to test it. The successful build meant the hypothesis was about to face its critical test.

Whether cap=1 would fix the regression or not, the process itself is the story: disciplined, data-driven, and architecture-aware. This is performance engineering at its finest — not guessing, but measuring; not accepting assumptions, but testing them; and never being afraid to revert a change that doesn't deliver, even when it was carefully planned and implemented.