Chunk 33.1
In this chunk, the assistant systematically wired the `cuzk` remote proving daemon into three core Curio task types: **PoRep (seal)**, **SnapDeals prove**, and **proofshare (PSProve)**. For each task, the pattern was consistent: add a `cuzkClient *cuzk.Client` field, modify the constructor to accept it, and update the `Do()` method to call `PoRepSnarkCuzk` (or equivalent) instead of the local SNARK function when the daemon is enabled. The `CanAccept()` method was adapted to query the daemon’s queue for backpressure, and `TypeDetails()` was changed to zero out local GPU/RAM requirements when `cuzk` is active, effectively bypassing Curio’s local resource accounting. The assistant worked iteratively, resolving LSP errors as they appeared—for example, adding missing imports and updating function signatures (`computeProof`, `computePoRep`, `computeSnap`) to accept the `*cuzk.Client` parameter. The edits progressed from the simpler PoRep and Snap tasks to the more complex proofshare task, where the `computeProof` function and its helpers were refactored to pass the client through. By the end of the chunk, all three task files had been updated, though the proofshare integration required several rounds of signature corrections. The themes of this chunk are **remote GPU offloading** and **task lifecycle adaptation**. The integration follows the earlier architectural plan: SNARK computation is delegated to the `cuzk` daemon while vanilla proof generation remains local. The use of backpressure via `CanAccept()` and zeroed resource costs in `TypeDetails()` ensures that Curio’s scheduler treats cuzk-enabled tasks as lightweight, relying on the daemon’s queue rather than local GPU availability. This chunk represents the core implementation step for the `cuzk` integration across all proof‑related tasks.
Wiring Remote GPU Proving into Curio: A Systematic Integration Journey
Message Articles
- The Verification Pivot: How a Single `go vet` Command Validated a Complex Integration
- The Pivot Point: Wiring a Remote Proving Daemon into Curio's Task Orchestrator
- The Read That Unlocks Integration: Wiring a Remote GPU Proving Daemon into Curio's PoRep Task
- The Unused Import: A Snapshot of Incremental Integration
- The Quiet Pivot: Wiring a Remote GPU Proving Daemon into Curio's Task Orchestrator
- The Critical Edit: Wiring Remote GPU Proving into Curio's PoRep Task
- The Backpressure Edit: Wiring Remote GPU Proving into Curio's Scheduler
- The Art of Zero: How a Single Edit Rerouted Curio's Resource Accounting for Remote GPU Proving
- The Verification Checkpoint: How a Single `go vet` Command Validated a Complex Integration
- The Pivot Point: Establishing a Pattern for Remote GPU Proving in Curio
- The Pivot Point: Reading the Snap Prove Task to Extend Remote GPU Offloading
- The Moment Before Completion: An LSP Error as a Window into Incremental Integration
- The Quiet Edit: Wiring Remote GPU Proving into Curio's SnapDeals Task
- The Quiet Edit: Wiring Remote GPU Proving into Curio's SnapDeals Task
- The Quiet Edit: Wiring Backpressure into Curio's SnapDeals Proving Pipeline
- The Quiet Edit: How Zeroing GPU Requirements in `TypeDetails()` Unlocks Remote Proving
- The Verification Checkpoint: A Single `go vet` Command in the Cuzk Integration Pipeline
- The Pivot: Transitioning to the Proofshare Task Integration
- Reading the Proofshare Task: The Final Wiring Step in Curio's Remote GPU Offloading
- Wiring the Proofshare Task: A Critical Juncture in Curio's cuzk Integration
- The Critical Edit: Wiring Remote GPU Proving into Curio's Proofshare Task
- The Signature That Didn't Match: Propagating the CUZK Client Through Proofshare's Call Chain
- The Cascading Signature Fix: Propagating a Client Parameter Through Curio's Proofshare Call Chain
- The Cascade of Signatures: Iterative Refactoring in the Proofshare Task
- The Last Signature in the Chain: Iterative Refactoring in the cuzk-Curio Integration
- The Final Stitch: Wiring Remote GPU Proving into Curio's Proofshare Task
- The Silence Between Actions: Interpreting an Empty Message in an AI-Assisted Coding Session