January 2026 monthly delivery focused on delivering a high-performance, quantized GEMM path within ROCm/aiter, including a fused GEMM kernel with A8W8 quantization, weight preshuffling, and split/concat outputs. This work, paired with robust config interfaces, tuned configurations (gfx942 defaults), and expanded test coverage, delivers measurable performance and flexibility improvements for matrix operations in ML workloads. Additionally, several reliability and maintainability improvements were made to the configuration surface and code organization.

2025-11 ROCm/aiter: Delivered a key feature that enhances performance and efficiency of tensor operations. Implemented a fused RMSNorm and FP8 per-tensor static quantization kernel in Triton, including a new kernel function and updates to the quantization logic. This work provides a more streamlined, low-latency path for quantized RMS normalization and FP8 quantization, improving throughput for transformer-like workloads. Also contributed to code quality through Python tooling formatting and cleanup. No major bugs fixed in this period are documented for this repo.