A compact, accurate, and bitwidth-programmable in-memory computing (IMC) static random-access memory (SRAM) macro, named CAP-RAM, is presented for energy-efficient convolutional neural network (CNN) inference. It leverages a novel charge-domain multiply-and-accumulate (MAC) mechanism and circuitry to achieve superior linearity under process variations compared to conventional IMC designs. The adopted semi-parallel architecture efficiently stores filters from multiple CNN layers by sharing eight standard 6T SRAM cells with one charge-domain MAC circuit. Moreover, up to six levels of bit-width of weights with two encoding schemes and eight levels of input activations are supported. A 7-bit charge-injection SAR (ciSAR) analog-to-digital converter (ADC) getting rid of sample and hold (S&H) and input/reference buffers further improves the overall energy efficiency and throughput. A 65-nm prototype validates the excellent linearity and computing accuracy of CAP-RAM. A single 512 × 128 macro stores a complete pruned and quantized CNN model to achieve 98.8% inference accuracy on the MNIST data set and 89.0% on the CIFAR-10 data set, with a 573.4-giga operations per second (GOPS) peak throughput and a 49.4-tera operations per second (TOPS)/W energy efficiency.

No abstract

According to a number of studies, use of a Reading Acceleration Program as reading intervention training has been demonstrated to improve reading speed and comprehension level effectively in most languages and countries. The objective of the current study was to provide further evidence of the effectiveness of a Reading Acceleration Program for Chinese children with reading disabilities using a distinctive Chinese reading acceleration training paradigm. The reading acceleration training paradigm is divided into a non-accelerated reading paradigm, a Character-accelerated reading paradigm and a Words-accelerated reading paradigm. The results of training Chinese children with reading disabilities indicate that the acceleration reading paradigm applies to children with Chinese-reading disabilities. In addition, compared with other reading acceleration paradigms, Words-accelerated reading training is more effective in helping children with reading disabilities read at a high speed while maintaining superior comprehension levels.

No abstract