Tensor core / MMA intrinsics

[tetsuo-cpp]

Summary

Add support for tensor core matrix multiply-accumulate (MMA) operations on modern NVIDIA GPUs.

Motivation

Tensor cores provide massive throughput for matrix operations (e.g., 16x16x16 matrix multiply in a single instruction). This is essential for competitive matmul performance on modern GPUs (Volta and later).

Design considerations

• WMMA (Warp Matrix Multiply Accumulate) API operates on matrix fragments
• Fragment types: a (M×K), b (K×N), c/d (M×N)
• Supported shapes: 16x16x16, 32x8x16, 8x32x16 (varies by GPU architecture)
• Need words for: load fragment, store fragment, MMA compute

Implementation notes

• Maps to nvvm.wmma or nvvm.mma intrinsics
• Requires floating-point support (depends on f16/f32 types)
• Fragment storage is distributed across warp lanes
• This is a significant feature that may need its own design document

Priority

Nice to have — needed for peak matmul performance but not for correctness.