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Conventional CMOS transistors will reach its power wall, a huge leakage power consumption limits the performance growth when technology scales down, especially beyond 45nm technology nodes. Spin based devices are one of the alternative computing technologies that aims to replace the current MOS based circuits by taking the advantage of their attractive(More)
Neuromorphic systems recently gained increasing attention for their high computation efficiency. Many designs have been proposed and realized with traditional CMOS technology or emerging devices. In this work, we proposed a spiking neuromorphic design built on resistive crossbar structures and implemented with IBM 130nm technology. Our design adopts a rate(More)
As manufacture process scales down rapidly, the design of <i>ternary content-addressable memory</i> (TCAM) requiring high storage density, fast access speed and low power consumption becomes very challenging. In recent years, many novel TCAM designs have been inspired by the research on emerging nonvolatile memory technologies, such as <i>magnetic tunneling(More)
Matrix-vector multiplication, as a key computing operation, has been largely adopted in applications and hence greatly affects the execution efficiency. A common technique to enhance the performance of matrix-vector multiplication is increasing execution parallelism, which results in higher design cost. In recent years, new devices and structures have been(More)
The applications of memristors in neuromorphic computing have been extensively studied for its analogy to synapse. To overcome sneak path issue, nonlinear resistive selectors have been introduced to the design of memristor crossbar, enabling a high integration density and robust computing capability. However, the nonlinearity of such selectors also(More)
As process technology continues scaling down, the memory barrier becomes more severe. Thus, spiking neuromorphic computing that can significantly enhance computing and communication efficiencies has been widely studied. Both conventional CMOS technology and emerging devices have been used in hardware implementation of spiking neuromorphic computing.(More)