The First Stone: Writing the Batch Collector for Phase 3 Cross-Sector Batching

Introduction

In the sprawling architecture of the cuzk pipelined SNARK proving engine — a system designed to generate Groth16 proofs for Filecoin's Proof-of-Replication (PoRep) at scale — there comes a moment when design meets execution. Message [msg 668] captures precisely that transition. It is the instant when the assistant, having spent several preceding messages exploring the codebase, absorbing its architecture, and carefully designing the Phase 3 cross-sector batching scheme, finally writes the first line of new code: a file called batch_collector.rs.

The message itself is deceptively brief:

[assistant] [write] /home/theuser/curio/extern/cuzk/cuzk-core/src/batch_collector.rs
Wrote file successfully.

LSP errors detected in other files:
<diagnostics file="/home/theuser/curio/extern/filecoin-ffi/proofs.go">
ERROR [1:1] go list failed to return CompiledGoFiles. This may indicate failure to perform cgo processing; try building at the command line. See https://golang.org/issue/38990.
ERROR [1001:10] cannot use 0 (untyped int constant) as cgo.RegisteredPoStProof value in return statement
ERROR [1052:10] cannot use 0 (untyped int constant) as cgo.RegisteredSealProof value ...

A single tool call, a confirmation of success, and then a cascade of LSP errors from an unrelated Go file. Yet beneath this surface simplicity lies the culmination of a deep technical investigation spanning multiple rounds of analysis, design, and planning. This article unpacks everything that this message represents: the reasoning that motivated it, the decisions that shaped it, the knowledge it presupposes, the knowledge it creates, and the thinking process that made it possible.

The Context: Why This Message Was Written

To understand why batch_collector.rs needed to exist, one must understand the problem it solves. The cuzk proving engine, as it existed at the end of Phase 2, had already achieved a significant architectural milestone: a true async-overlap pipeline where CPU-bound circuit synthesis for proof N+1 ran concurrently with GPU-bound proving for proof N. This yielded a 1.27x throughput improvement over sequential execution on an RTX 5070 Ti, with three consecutive 32 GiB PoRep proofs completing in ~212.7 seconds (see [chunk 11.0]).

However, the Phase 2 pipeline still processed proofs one at a time. Each proof required its own full synthesis pass — building all 10 partition circuits for a single sector, running bellperson::synthesize_circuits_batch(), producing intermediate state, and then sending that state to the GPU for proving. The GPU, with its massive parallel compute capacity, was often underutilized because each individual proof's GPU work was bounded by the size of a single sector's circuit.

The key insight for Phase 3 was that cross-sector batching could dramatically improve throughput by combining multiple sectors' circuits into a single synthesis pass and a single GPU proving call. Instead of proving one sector at a time, the engine could accumulate multiple PoRep requests from different sectors, synthesize all their circuits together (N sectors × 10 partitions each), and prove the combined result in one GPU invocation. After proving, the concatenated proof bytes would be split back into per-sector results.

This is the problem that batch_collector.rs was written to solve. It is the architectural glue that enables the transition from per-sector processing to cross-sector batching.

The Design Decisions Embedded in This Message

The decision to create a dedicated batch_collector module — rather than embedding batching logic into the existing scheduler.rs or engine.rs — reflects a deliberate architectural choice. The assistant's design summary in [msg 667] reveals the reasoning:

"The key insight is that cross-sector batching works at the engine level, not the gRPC API level. The daemon already accepts individual proof requests. Phase 3 adds a batch collector between the scheduler and synthesis task that accumulates same-type PoRep requests..."

This separation of concerns is critical. The scheduler (in scheduler.rs) is responsible for dispatching proof requests to GPU workers with priority ordering. The engine (in engine.rs) is the central coordinator that owns the scheduler, GPU workers, and SRS manager. The batch collector sits between them — it intercepts proof requests of the same circuit type (PoRep, and later SnapDeals), accumulates them until a configurable threshold is reached, and then flushes the batch as a single unit to the synthesis pipeline.

Several design decisions are implicit in this architecture:

1. Batchable vs. non-batchable proofs: WinningPoSt and WindowPoSt proofs are priority-critical — they have strict timing requirements for Filecoin consensus. The batch collector must allow these to preempt-flush any pending batch and process immediately. Only PoRep (and SnapDeals) benefit from batching.
2. Configurable thresholds: The existing config.rs already had scheduler.max_batch_size and scheduler.max_batch_wait_ms fields, placed there during Phase 2 as forward-looking hooks. The batch collector now gives these fields meaning.
3. Backward compatibility: Setting max_batch_size=1 must preserve Phase 2 behavior exactly. The batch collector is an optimization, not a behavioral change.
4. Timing accuracy: Each caller must receive its individual proof with accurate timings, even when proofs are batched together. This requires careful tracking of per-sector start and end times.

Assumptions Made

The assistant makes several assumptions in writing this message:

That the batch collector is the correct abstraction. Could batching logic have been embedded directly in the engine's synthesis task loop? Possibly, but that would couple batching policy with synthesis execution, making it harder to test, configure, or extend. The dedicated module provides a clean interface.

That the config fields already exist. The assistant assumes that max_batch_size and max_batch_wait_ms are already present in the config struct and are ready to be consumed. This is confirmed by reading config.rs in [msg 663].

That the LSP errors are pre-existing and irrelevant. The errors shown are from /home/theuser/curio/extern/filecoin-ffi/proofs.go — a Go file in a completely different project (the Filecoin FFI layer). These are Go compilation errors related to cgo constant type mismatches. They have nothing to do with the Rust code being written. The assistant correctly ignores them.

That the batch collector will be consumed by subsequent changes. Writing batch_collector.rs is only the first step. The assistant assumes that it will next modify engine.rs to integrate the batch collector, add synthesize_porep_c2_multi() to pipeline.rs, and add split_batched_proofs() for proof separation. These are tracked in the todo list visible in [msg 667].

Input Knowledge Required

To understand this message, a reader needs familiarity with several domains:

The cuzk project architecture: The workspace has five crates (cuzk-proto, cuzk-core, cuzk-server, cuzk-daemon, cuzk-bench) with cuzk-core containing the engine, pipeline, scheduler, SRS manager, and types modules. The batch collector lives in cuzk-core/src/.

The Phase 2 pipeline: The existing pipeline splits proving into CPU-bound synthesis (building circuits, running bellperson::synthesize_circuits_batch()) and GPU-bound proving (running the Groth16 prover on the synthesized assignments). These communicate via a bounded tokio channel for backpressure.

The Filecoin proof types: PoRep (Proof-of-Replication) is the primary batchable proof, requiring 10 partition circuits per sector. WinningPoSt and WindowPoSt are time-sensitive proofs that must not be delayed by batching. SnapDeals is a newer proof type for sector updates.

The bellperson fork: The project uses a minimal fork of bellperson that exposes private synthesis/assignment internals (ProvingAssignment, synthesize_circuits_batch, prove_from_assignments) that the upstream library keeps hidden. This fork is what enables the split synthesis/GPU pipeline.

The SRS manager: The SrsManager handles loading and caching of Groth16 parameters (.params files) for each circuit type. The SRS is ~47 GiB pinned in GPU memory and is shared across all proofs — a critical factor in why cross-sector batching has sub-linear memory growth.

Output Knowledge Created

This message creates the batch_collector.rs file — a new module in the cuzk-core crate. While the file's full contents are not displayed in this message (the write tool only confirms success), subsequent messages in the conversation would reveal its implementation. Based on the design summary in [msg 667] and the chunk summary for segment 11, we know the batch collector provides:

• A BatchCollector struct that accumulates ProofRequest values keyed by circuit type
• A flushing mechanism triggered by max_batch_size (accumulate N requests) or max_batch_wait_ms (timeout since first request)
• Preempt-flush behavior for non-batchable proof types (WinningPoSt, WindowPoSt)
• A method to drain the accumulated batch and send it to the synthesis pipeline as a single unit
• Thread-safe access via Arc<Mutex<BatchCollector>> for sharing between the engine's synthesis task and the gRPC service The batch collector is the foundational piece upon which the rest of Phase 3 is built. Without it, the engine has no mechanism to accumulate requests across sectors. With it, the engine can implement the full batching pipeline: accumulate → batch-synthesize → GPU-prove → split proofs → return to callers.

The Thinking Process Visible in the Reasoning

The assistant's thinking process is most visible in the messages leading up to [msg 668]. In [msg 661], the assistant launches a comprehensive exploration task to read all source files in the cuzk codebase. In <msg id=662-664>, it reads key files directly — engine.rs, pipeline.rs, config.rs, types.rs, scheduler.rs, lib.rs, srs_manager.rs, and the bench and server files. This is a systematic reconnaissance phase: the assistant is building a mental model of the existing code before making any changes.

In [msg 665], the assistant updates its todo list to reflect the design phase. In [msg 666], it reads the protobuf definition and workspace Cargo.toml to understand the API layer and dependency structure. Finally, in [msg 667], it produces a detailed design summary:

"The key insight is that cross-sector batching works at the engine level, not the gRPC API level. The daemon already accepts individual proof requests. Phase 3 adds a batch collector between the scheduler and synthesis task that accumulates same-type PoRep requests..."

This design summary reveals the assistant's reasoning process. It has identified that the gRPC API (defined in proving.proto) accepts individual proof submissions — and changing the API to accept batches would break backward compatibility and require coordinated changes across Curio's Go layer, the protobuf definitions, and the Rust service implementation. Instead, the assistant chooses to keep the API unchanged and add batching as an internal optimization. This is a pragmatic, minimally-invasive design.

The assistant also identifies exactly which files need to change and in what order:

1. batch_collector.rs — new module (this message)
2. pipeline.rs — new synthesize_porep_c2_multi() function
3. engine.rs — integrate batch collector into synthesis task
4. config.rs — use existing max_batch_size and max_batch_wait_ms fields
5. types.rs — minor additions for batched result tracking This ordering reflects a dependency-aware approach: write the new module first, then add the pipeline function that it will call, then integrate into the engine, then wire up configuration, then add any type changes needed.

The Significance of This Moment

Message [msg 668] is significant because it marks the boundary between analysis and action. The preceding messages were about reading, understanding, and designing. This message is about creating. The batch_collector.rs file is the first tangible artifact of Phase 3 — the first line of new code in a sequence that will ultimately deliver a 1.46x throughput improvement over the Phase 2 baseline (as validated by subsequent GPU E2E testing documented in [chunk 11.1]).

The LSP errors displayed alongside the success message serve as a reminder of the messy reality of working in a large codebase. The filecoin-ffi Go errors are irrelevant noise — they exist in a different language, a different project, and a different directory. But they appear in the assistant's context because the LSP server scanned the entire workspace. The assistant's ability to ignore these distractions and focus on the task at hand is itself a form of engineering judgment.

In the broader narrative of the cuzk project, this message is the first step toward transforming the proving engine from a per-sector pipeline into a cross-sector batching system. The roadmap extends through Phase 4 (compute optimizations like SmallVec and parallel MSMs) and Phase 5 (Pre-Compiled Constraint Evaluator), but none of those phases would be possible without the architectural foundation laid here. The batch collector is the keystone — small in isolation, but everything else depends on it.