[QDP] [Feature] Multi-GPU Data-Parallel Encoding for Scalable Quantum State Preparation

[400Ping]

Summary

Propose adding multi-GPU data-parallel encoding to QDP so users can scale quantum state preparation across multiple GPUs. Currently, QdpEngine only supports a single device_id, which limits throughput for large batches and high qubit counts (e.g., 20+ qubits).

Motivation

• Current limitation: QdpEngine::new(device_id: usize) accepts only one GPU (qdp-core/src/lib.rs).
• Use case: High-qubit encoding (20+ qubits) and large batches hit single-GPU memory and compute limits. Multi-GPU parallel encoding can increase throughput proportionally.
• Alignment with PR [QDP] Add a Quantum Data Loader and API refactor #1000: The Quantum Data Loader (PR [QDP] Add a Quantum Data Loader and API refactor #1000) provides batch-by-batch iteration; multi-GPU support would allow batches to be distributed across GPUs for an end-to-end, high-throughput pipeline.

Proposed Design

• Batch routing: Distribute batches across GPUs (e.g., round-robin or workload-aware).
• Result aggregation: Merge outputs from each GPU into a single DLPack tensor (or keep a distributed representation for downstream use).
• Stream management: Each GPU uses its own CUDA stream to avoid synchronization bottlenecks.

Scope

qdp-core (Rust)

• Add a multi-GPU engine abstraction (e.g., QdpEnginePool) to manage multiple QdpEngine instances.
• Implement encode_batch_distributed to split batches across GPUs or assign different batches to different GPUs.
• Use rayon or std::thread for CPU-side coordination.

qdp-python

• Expose a new API (e.g., QdpEngine(device_ids=[0, 1, 2]) or MultiGpuEngine).
• Integrate with the Quantum Data Loader once PR [QDP] Add a Quantum Data Loader and API refactor #1000 is merged.
• Preserve backward compatibility when a single device is specified.

Non-Goals (out of scope)

• Multi-GPU model parallelism or tensor parallelism within a single encoding operation.
• Automatic GPU selection or load balancing in the first version (can be added later).