>Those have failed by being impossible to program.
I think you spoke too soon about their failure, sooner they will be much easier to program [1].
Interestingly, Nvidia GPU now is also moving to tile-based GPU programming model that targets portability for NVIDIA Tensor Cores [2]. Recently there're discussions on the topic at HN [3].
[1] Developing a BLAS Library for the AMD AI Engine [pdf]:
The amd npu and versal ML tiles (same underlying architecture) have been an complete failure. Dynamic programming models like cu tile do not work on them at all, be cause they require an entirely static graph to function. AMD is going to walk away from their NPU architecture and unify around their GPU IP on inference products in the future.
I think you spoke too soon about their failure, sooner they will be much easier to program [1].
Interestingly, Nvidia GPU now is also moving to tile-based GPU programming model that targets portability for NVIDIA Tensor Cores [2]. Recently there're discussions on the topic at HN [3].
[1] Developing a BLAS Library for the AMD AI Engine [pdf]:
https://uni.tlaan.nl/thesis/msc_thesis_tristan_laan_aieblas....
[2] NVIDIA CUDA Tile:
https://developer.nvidia.com/cuda/tile
[3]CUDA Tile Open Sourced (103 comments):
https://news.ycombinator.com/item?id=46330732