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2012 iv Organic Light Emitting Diode (OLED) has emerged as a new generation of display techniques for mobile devices. Emitting light with organic fluorescent materials OLED display panels are thinner, brighter, lighter, cheaper and more power efficient, compared to other display technologies such as Liquid Crystal Displays (LCD). In present mobile devices,(More)
—With the scaling of technology and the need for higher performance and more functionality, power dissipation is becoming a major bottleneck for microprocessor designs. Because clock power can be significant in high-performance processors , we propose a deterministic clock-gating (DCG) technique which effectively reduces clock power. DCG is based on the key(More)
High demand for computation resources severely hinders deployment of large-scale Deep Neural Networks (DNN) in resource constrained devices. In this work, we propose a Structured Sparsity Learning (SSL) method to regularize the structures (i.e., filters, channels, filter shapes, and layer depth) of DNNs. SSL can: (1) learn a compact structure from a bigger(More)
In recent years, many systems have employed NAND flash memory as storage devices because of its advantages of higher performance (compared to the traditional hard disk drive), high-density, random-access, increasing capacity, and falling cost. On the other hand, the performance of NAND flash memory is limited by its “erase-before-write”(More)
With the scaling of technology and the need for higher performance and more functionality, power dissipation is becoming a major bottleneck for microprocessor designs. Pipeline balancing (PLB), a previous technique, is essentially a methodology to clock-gate unused components whenever a program's instruction-level parallelism is predicted to be low.(More)
In recent years, non-volatile memory (NVM) technologies have emerged as candidates for future universal memory. NVMs generally have advantages such as low leakage power, high density, and fast read spead. At the same time, NVMs also have disadvantages. For example, NVMs often have asymetric read and write speed and energy cost, which poses new challenges(More)
The Brain-State-in-a-Box (BSB) model is an auto-associative neural network that has been widely used in optical character recognition and image processing. Traditionally, the BSB model was realized at software level and carried out on high-performance computing clusters. To improve computation efficiency and reduce resources requirement, we propose a(More)
By mimicking the highly parallel biological systems, neuromorphic hardware provides the capability of information processing within a compact and energy-efficient platform. However, traditional Von Neumann architecture and the limited signal connections have severely constrained the scalability and performance of such hardware implementations. Recently,(More)
Spin-Transfer Torque Random Access Memory (STT-RAM) demonstrated great potentials as an universal memory for its fast access speed, zero standby power, excellent scalability and simplicity of cell structure. However, large process variations of both magnetic tunneling junction and CMOS process severely limit the yield of STT-RAM chips and prevent the(More)
We proposed a novel self-reference sensing scheme for Spin-Transfer Torque Random Access Memory (STT-RAM) to overcome the large bit-to-bit variation of Magnetic Tunneling Junction (MTJ) resistance. Different from all the existing schemes, our solution is nondestructive: The stored value in the STT-RAM cell does NOT need to be overwritten by a reference(More)