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My summary:

* deephi built an FPGA based processing unit specialized for sparse low precision tensor operations

* Now they have a dev kit for turning your tensorflow/caffe/mxnet models into compressed (sparse/low precision) binaries that are optimized to run on their processors.

They published a paper about how they balance compression/accuracy. [0]

[0] https://arxiv.org/pdf/1612.00694.pdf



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