[DISCUSS] TVM Core Strategy for Emerging Needs

In my personal feeling, TVM’s momentum was at a peak around 2019-2020, but went down afterwards. I can’t speak for others, but for myself, I can’t keep contributing to TVM since 2021 because my team switched the gear to work on distributed training, which was popular by that time, but we felt it would be time consuming to propose and upstream training support (it turns out to be true if you look at Relax). Finally we worked on our own codebase and gradually got away from TVM upstream.

On the other hand, I recently found that TVM’s momentum goes up again along with the brand “MLC-LLM”, just because a few community members make some efforts to release a high-performance chat bot app of Llama-2 powered by TVM unity. This to me is a role model that shows the importance of catching up the workloads/applications most people care in order to stay on SOTA.

Consequently, it would be great and happy to see TVM unity becomes the official main branch, so that it’s likely to further accelerate the developments of LLM related features. For example, serving a LLM with tensor parallelism and quantization would be extremely important in the upcoming 6 months. NVIDIA is going to release TensorRT-LLM next week, it would be a big bump if MLC-LLM is able to be competitive.

My two cents.

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