AIRCHITECT: Learning Custom Architecture Design and Mapping Space

no code implementations • 16 Aug 2021 • Ananda Samajdar, Jan Moritz Joseph, Matthew Denton, Tushar Krishna

We design and train a custom network architecture called AIRCHITECT, which is capable of learning the architecture design space with as high as 94. 3% test accuracy and predicting optimal configurations which achieve on average (GeoMean) of 99. 9% the best possible performance on a test dataset with $10^5$ GEMM workloads.

Direct Spatial Implementation of Sparse Matrix Multipliers for Reservoir Computing

no code implementations • 21 Jan 2021 • Matthew Denton, Herman Schmit

We have implemented these matrices on a large FPGA and provide a cost model that is simple and extensible.