aloha1357 opened a new pull request, #1387: URL: https://github.com/apache/mahout/pull/1387
### Related Issues <!-- Closes #123 --> related #1385 ### Changes - [ ] Bug fix - [ ] New feature - [x] Refactoring - [ ] Documentation - [ ] Test - [ ] CI/CD pipeline - [ ] Other ### Why As part of the IQP Encoding Optimization PR Split Plan, PR 2 focuses on "Batch throughput optimization" and lays the structural groundwork for Tensor Core (TC) acceleration (which will be fully introduced in PR 5 & 6). **Architectural Philosophy: Dual-Path Explicit Opt-in** It is crucial to note that these new Tensor Core optimizations do *not* automatically replace or override the existing standard algorithms. We are adopting a **Dual-Path Architecture**: 1. **Standard Path (`encode_batch`):** The original, hardware-agnostic FP64 FWT path is fully preserved. This ensures that users on older hardware (without Tensor Cores) or those requiring strict IEEE 754 standard FP64 behavior without any mixed-precision artifacts can continue running unmodified. 2. **Tensor Core Path (`encode_batch_tc`):** This is a new, highly specialized API path introduced here. Because Tensor Cores utilize INT8 mixed-precision arithmetic (compensated via the Chinese Remainder Theorem later in PR 6), there are microscopic floating-point differences. In HPC and quantum simulation, auto-dispatching to mixed-precision can cause difficult-to-debug numerical artifacts. Therefore, the TC pipeline is strictly an **explicit opt-in** for advanced users seeking maximum throughput on supported hardware (Turing/Ampere/Hopper). To prepare for this `encode_batch_tc` pipeline, we need a robust scaffolding for batch data transformation. The original code processed matrices sequentially; this refactoring introduces batched layouts and kernels required for the Kronecker-based matrix multiplication that Tensor Cores will eventually execute. ### How - **Created `iqp_tc.cu`:** Introduced new kernels specifically designed to manage memory layout for batched operations. - **Phase Split Kernel (`iqp_phase_split_kernel`):** Unrolls the batch and splits the initial phase computation into pure real and imaginary parts to prepare for INT8 matrix multiplication. - **Batch Transpose Kernel (`iqp_tc_batch_transpose_kernel`):** Implemented a Shared Memory Bank-Conflict-Free matrix transpose kernel, essential for efficiently reordering data between Tensor Core FWT stages. - **Recombine Kernel (`recombine_complex_kernel`):** Restores the split real and imaginary parts back into the standard `cuDoubleComplex` format expected by downstream processes. - **Rust Integration:** Updated `lib.rs` and `iqp.rs` to expose and call the new `launch_iqp_encode_tc` function from Rust, laying the structural groundwork for the full Tensor Core pipeline. ## Checklist - [x] Added or updated unit tests for all changes (Verified that existing tests pass, and batching logic doesn't break `qdp-core`) - [x] Added or updated documentation for all changes (Added explicit comments describing the purpose of the new kernels) -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
