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As computations in machine-learning applications are increasing simultaneously along the size of datasets, the energy and performance costs of data movement dominate that of compute. This issue is more pronounced in embedded systems with limited ...

With fully autonomous flight capabilities coupled with user-specific applications, drones, in particular quadcopter drones, are becoming prevalent solutions in myriad commercial and research contexts. However, autonomous drones must operate within ...

A key real-time task in autonomous systems is simultaneous localization and mapping (SLAM). Although prior work has proposed hardware accelerators to process SLAM in real time, they paid less attention to power consumption. To be more power-efficient, ...

Sparse computations dominate a wide range of applications from scientific problems to graph analytics. The main characterization of sparse computations, indirect memory accesses, prevents them from effectively achieving high performance on general-...

The performance of sparse problems suffers from lack of spatial locality and low memory bandwidth utilization. However, the distribution of non-zero values in the data structures of a class of sparse problems, such as matrix operations in neural ...