The Quiet Fix: Tuning Synthesis Concurrency for GPU Proving Throughput

A Single Line Change That Unlocked the Pipeline

In a sprawling, multi-month effort to build a high-performance CUDA-based zero-knowledge proving daemon (cuzk) for Filecoin's proof-of-replication (PoRep) and related proof types, the assistant dispatched a series of surgical configuration fixes. Among them, message [msg 3723] stands out for its deceptive simplicity:

[edit] /tmp/czk/docker/cuzk/benchmark.sh Edit applied successfully.

That is the entire message. A tool call result notification, barely a line of text. Yet this single edit—changing SYNTHESIS_CONCURRENCY=4 to SYNTHESIS_CONCURRENCY=18 in the benchmark script—represents the culmination of weeks of deep system debugging, performance analysis, and iterative tuning. To understand why a four-fold increase in a concurrency parameter matters, one must understand the extraordinary complexity of the system it controls.

The Context: A GPU Proving Pipeline Under the Microscope

The cuzk daemon is a specialized piece of infrastructure designed to accelerate Filecoin's storage proof generation using NVIDIA GPUs. The proving pipeline has two major stages: synthesis (CPU-bound computation that transforms witness data into constraint system artifacts) and GPU proving (CUDA kernel execution for NTT and MSM operations). These stages are decoupled by a dispatch queue, regulated by a PI-controlled pacer that the assistant had spent the previous [msg 3717] segments designing and debugging.

The assistant had already resolved a critical GPU underutilization bug—the root cause was that cudaMemcpyAsync from unpinned heap memory forced CUDA to stage data through a tiny internal bounce buffer, achieving only 1–4 GB/s instead of the PCIe Gen5 line rate of ~50 GB/s. A pinned memory pool fixed that, collapsing per-partition NTT+MSM time from 8–19 seconds to under one second. But fixing the transfer bottleneck exposed a new constraint: the synthesis stage, which feeds the GPU pipeline, was itself a bottleneck.

Why 4 Was Wrong and 18 Was Right

The synthesis_concurrency parameter controls how many proof synthesis tasks can run simultaneously. Each synthesis consumes significant CPU resources—a single proof takes 20–60 seconds depending on CPU contention—and also allocates substantial memory (roughly 14 GiB for PoRep partitions, 9 GiB for SnapDeals). Setting this value too low starves the GPU pipeline, leaving the GPU idle while waiting for synthesis to produce work. Setting it too high causes CPU contention that slows every synthesis down, creating a self-defeating bottleneck.

The assistant's earlier work had established that 18 concurrent syntheses is the sweet spot for DDR5 systems with 64 cores (see [msg 3717]). This was not a guess but a finding from extensive tuning, hard-capped via the max_parallel_synthesis configuration parameter (also defaulting to 18). The original value of 4 had been carried over from earlier development iterations when the system was smaller and the GPU pipeline was not yet the primary concern. With the pinned memory pool and PI-controlled pacer now operational, the synthesis stage had become the gating factor.

The edit in [msg 3723] applies this same fix to benchmark.sh, the script used for performance benchmarking on vast.ai instances. The companion fix to run.sh (the production daemon launcher) had already been applied in the preceding message [msg 3722]. Both scripts needed the same correction because they serve different roles: run.sh starts the daemon for continuous operation, while benchmark.sh runs a controlled performance test. Inconsistent defaults between them would produce misleading benchmark results that don't reflect production behavior.

The Reasoning Behind the Edit

The assistant's decision to make this change was grounded in a clear chain of reasoning:

Observation: Live deployment testing revealed that GPU utilization was still suboptimal despite the pinned memory pool fix. The GPU workers showed idle gaps between partition proves.
Diagnosis: The PI-controlled dispatch pacer (built in earlier segments) was correctly regulating GPU queue depth, but the synthesis stage could not keep up because it was limited to only 4 concurrent proofs.
Prior knowledge: Earlier tuning had established that 18 concurrent syntheses was the optimal value for the target hardware (64-core DDR5 systems). This was already reflected in the max_parallel_synthesis config parameter but had not been propagated to the synthesis_concurrency default in the shell scripts.
Action: Change SYNTHESIS_CONCURRENCY=4 to SYNTHESIS_CONCURRENCY=18 in both run.sh and benchmark.sh. The edit to benchmark.sh (message [msg 3723]) was the second of these two changes, applied immediately after run.sh succeeded.

Input Knowledge Required

To understand why this edit matters, one needs to know:

The two-stage pipeline architecture of cuzk: CPU-bound synthesis feeds a GPU queue, and the GPU processes partitions one at a time (or a few with concurrent kernels). The synthesis stage must produce work fast enough to keep the GPU busy.
The memory architecture: SRS (~44 GiB pinned), PCE (~26 GiB heap), and per-partition working memory (~14 GiB for PoRep, ~9 GiB for SnapDeals). Running too many syntheses concurrently risks OOM.
The dispatch pacer: A PI controller that monitors GPU queue depth and adjusts the rate at which syntheses are dispatched. It works best when the synthesis stage can sustain a steady flow of work.
The deployment context: These scripts run on vast.ai instances with 64 cores, DDR5 RAM, and NVIDIA RTX 5090 GPUs connected via PCIe Gen5. The synthesis_concurrency parameter is distinct from max_parallel_synthesis (which caps partition-level syntheses across all proofs).

Output Knowledge Created

This edit, combined with its companion in run.sh, ensures that:

Production and benchmark configurations are consistent. Both scripts now default to 18 concurrent syntheses, so benchmarks accurately reflect production behavior.
The GPU pipeline is adequately fed. With 18 concurrent syntheses, the synthesis stage can produce work fast enough to keep the GPU busy, maximizing throughput.
The PI-controlled dispatch pacer operates in its designed regime. The pacer was tuned assuming sufficient synthesis throughput; starving it with too few syntheses would cause the pacer to oscillate or under-deliver.

Assumptions and Potential Mistakes

The assistant assumed that 18 is the universally correct value for all target machines. This is a reasonable assumption given that the target deployment is homogeneous (same CPU, same memory architecture, same GPU), but it could be wrong if:

Instances have fewer cores or slower memory, making 18 too aggressive and causing CPU thrashing.
Instances have more cores or faster memory, leaving headroom for even higher concurrency.
The proof type mix changes (e.g., more SnapDeals, which use less memory per partition), allowing higher concurrency without OOM risk. The assistant mitigated this by also setting max_parallel_synthesis = 18 as a hard cap, and by making synthesis_concurrency a configurable parameter rather than a compile-time constant. But the default value of 18 is baked into the shell scripts, which means operators who don't override it get this value regardless of their hardware. Another subtle assumption: that the benchmark should use the same concurrency as production. This is defensible—benchmarks should reflect real performance—but it means benchmark results include the effects of CPU contention from 18 concurrent syntheses, which might not be desirable if the goal is to measure peak GPU throughput in isolation.

The Broader Significance

What makes [msg 3723] noteworthy is not the edit itself but what it represents. This single line change is the final adjustment in a long chain of performance optimizations that transformed the cuzk proving pipeline:

Phase 1: Implement priority-based scheduling and FIFO dispatch.
Phase 2: Diagnose GPU underutilization, build pinned memory pool, achieve near-zero H2D transfer times.
Phase 3: Build PI-controlled dispatch pacer to stabilize GPU queue depth.
Phase 4: Tune PI controller parameters, add re-bootstrap logic, set max_parallel_synthesis cap.
Phase 5: Fix deployment configuration issues—including this edit—to make all the above work correctly in production. The edit in [msg 3723] is the point where all the earlier engineering effort pays off. Without the correct synthesis_concurrency, the pinned memory pool and PI pacer would be underutilized, and the GPU would still show idle gaps. With it, the entire pipeline can run at full capacity.

Conclusion

Message [msg 3723] is a study in how the most impactful changes are often the simplest. A one-line edit to a shell script, changing a number from 4 to 18, unlocked the full performance of a GPU proving pipeline that had been meticulously optimized across dozens of commits and thousands of lines of code. It is a reminder that in complex systems, configuration parameters are not arbitrary settings—they are the interface between architectural design and operational reality. Getting them wrong means the architecture never works as intended. Getting them right means the system sings.