Coarse-Grained Reconfigurable Architectures (CGRA) is a promising solution for accelerating
computation intensive tasks due to its good trade-off in energy efficiency and flexibility. …

A radiation harden technique based on gate sizing and multi-objective genetic algorithm (MOGA)
is developed to optimize the soft error tolerance of standard cell circuits. Soft error rate (…

Deep learning accelerators have emerged to enable energy-efficient and high-throughput
inference from edge devices such as self-driving cars and smartphones, to data centers for …

Automatic ship detection in optical remote-sensing (ORS) images has wide applications in
civil and military fields. Research on ship detection in ORS images started late compared to …

Fail-slow hardware is an under-studied failure mode. We present a study of 114 reports of
fail-slow hardware incidents, collected from large-scale cluster deployments in 14 institutions. …

Remarkable progress has been made in image classification and segmentation, due to the
recent study of deep convolutional neural networks (CNNs). To solve the similar problem of …

Much attention is being paid to using high-performance convolutional neural networks (CNNs)
in the area of ship detection in optical remoting sensing (ORS) images. However, the …

Convolutional neural networks (CNNs) have had great success when applied to computer
vision technology, and many application-specific integrated circuit (ASIC) and field-…

Due to the winding level of the thinned wafers and the surface roughness of silicon dies, the
quality of through-silicon vias (TSVs) varies during the fabrication and bonding process, …

A pare to optimal temporal partition methodology was developed for splitting and mapping
large data flow graph (DFG) to the coarse-grained reconfigurable architecture (CGRA). A multi…