Three tracks: monthly suite digests, bylined technical deep-dives from sub-project maintainers when non-trivial work ships, and occasional thinking pieces about Trainium's place in the accelerator landscape.
The editorial stance is explicit: we write about what worked and what didn't. Blind alleys, reverted kernels, surprises from the Neuron compiler, numbers that disappointed us — all of that belongs in these pages. Vendor-marketing voice isn't useful to anyone building on this suite.
AUTHOR_BRIEF.md for the editorial brief and _template.md for a starter file.comments: true accept threaded comments via giscus (GitHub Discussions).The trnsci scientific computing suite for AWS Trainium is public. Six libraries covering the CUDA cu* equivalents the Neuron SDK ships without, a coordinating meta-package, full docs, seven PyPI packages, a conda-forge submission in review, and a five-phase roadmap from current alpha to generation-tuned stable. This is the first post of a blog series that will tell the project's story as it unfolds.