Bingjun Xiao

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Convolutional neural network (CNN) has been widely employed for image recognition because it can achieve high accuracy by emulating behavior of optic nerves in living creatures. Recently, rapid growth of modern applications based on deep learning algorithms has further improved research and implementations. Especially, various accelerators for deep CNN have(More)
One of the necessary requirements for the placement process is that it should be capable of generating routable solutions. This paper describes a simple but effective method leading to the reduction of the routing congestion and the final routed wirelength for large-scale mixed-size designs. In order to reduce routing congestion and improve routability, we(More)
High-level synthesis (HLS) tools have made significant progress in compiling high-level descriptions of computation into highly pipelined register-transfer level (RTL) specifications. The high-throughput computation raises a high data demand. To prevent data accesses from being the bottleneck, on-chip memories are used as data reuse buffers to reduce(More)
Application-specific accelerators provide orders-of-magnitude improvement in energy-efficiency over CPUs, and accelerator-rich computing platforms are showing promise in the dark silicon age. Memory sharing among accelerators leads to huge transistor savings, but needs novel designs of interconnects between accelerators and shared memories. Accelerators run(More)
Future processor chips will not be limited by the transistor resources, but will be mainly constrained by energy efficiency. Reconfigurable fabrics bring higher energy efficiency than CPUs via customized hardware that adapts to user applications. Among different reconfigurable fabrics, coarse-grained reconfigurable arrays (CGRAs) can be even more efficient(More)
State-of-charge (SOC) measures energy left in a battery, and it is critical for modeling and managing batteries. Developing efficient yet accurate SOC algorithms remains a challenging task. Most existing work uses regression based on a time-variant circuit model, which may be hard to converge and often does not apply to different types of batteries. Knowing(More)
Application-specific accelerators provide 10-100× improvement in power efficiency over general-purpose processors. The accelerator-rich architectures are especially promising. This work discusses a prototype of accelerator-rich CMPs (PARC). During our development of PARC in real hardware, we encountered a set of technical challenges and proposed(More)