March 2026 monthly summary for pytorch/pytorch: Delivered a meta kernel for the backward pass of the scaled dot product fused attention, addressing dynamo tracing issues and expanding support for varying tensor shapes. This work improves transformer reliability and throughput, particularly for dynamic shapes and large-scale models. CI validation completed; PR 178494 merged with differential revision D96939382. This contribution strengthens the PyTorch attention kernel stack for both training and inference.

June 2025 monthly summary for pytorch/torchrec. Focused on delivering MTIA support within TorchRec sharding to enable efficient resource management across heterogeneous hardware configurations. Implemented MTIA as a compute device and updated storage mapping and memory-type handling to align MTIA with CUDA for memory allocation and storage management. This work lays the groundwork for multi-tiered inference architecture deployments and cross-device resource optimization.

May 2025: Delivered MTIA Device Properties API for PyTorch, introducing a getDeviceProperties API to retrieve MTIA device properties. This enhancement improves observability, debugging, and optimization workflows for MTIA hardware. The work was implemented in graphcore/pytorch-fork, establishing a foundation for enhanced MTIA device management and future feature expansion.