Easy and Efficient Transformer : Scalable Inference Solution For large NLP model

Recently, large-scale transformer-based models have been proven to be effective over a variety of tasks across many domains. Nevertheless, putting them into production is very expensive, requiring comprehensive optimization techniques to reduce inference costs. This paper introduces a series of transformer inference optimization techniques that are both in algorithm level and hardware level. These techniques include a pre-padding decoding mechanism that improves token parallelism for text generation, and highly optimized kernels designed for very long input length and large hidden size. On this basis, we propose a transformer inference acceleration library -- Easy and Efficient Transformer (EET), which has a significant performance improvement over existing libraries. Compared to Faster Transformer v4.0's implementation for GPT-2 layer on A100, EET achieves a 1.5-4.5x state-of-art speedup varying with different context lengths. EET is available at https://github.com/NetEase-FuXi/EET. A demo video is available at https://youtu.be/22UPcNGcErg

The Design and Experimentation of a Corn Moisture Detection Device Based on Double Capacitors

Detecting the moisture content of grain accurately and rapidly has important significance for harvesting, transport, storage, processing, and precision agriculture. There are some problems with the slow detection speeds, unstable detection, and low detection accuracy of moisture contents in corn harvesters. In that case, an online moisture detection device was designed, which is based on double capacitors. A new method of capacitance complementation and integration was proposed to eliminate the limitation of single data. The device is composed of a sampling mechanism and a double-capacitor sensor consisting of a flatbed capacitor and a cylindrical capacitor. The optimum structure size of the capacitor plates was determined by simulation optimization. In addition to this, the detection system with software and hardware was developed to estimate the moisture content. Indoor dynamic measurement tests were carried out to analyze the influence of temperature and porosity. Based on the influencing factors and capacitance, a model was established to estimate the moisture content. Finally, the support vector machine (SVM) regressions between the capacitance and moisture content were built up so that the R2 values were more than 0.91. In the stability test, the standard deviation of the stability test was 1.09%, and the maximum relative error of the measurement accuracy test was 1.22%. In the dynamic verification test, the maximum error of the measurement was 4.62%, less than 5%. It provides a measurement method for the accurate, rapid, and stable detection of the moisture content of corn and other grains

Visible-Light Active and Magnetically Recyclable Nanocomposites for the Degradation of Organic Dye

Recyclable visible-light photocatalyst Fe3O4@TiO2 with core-shell structure was prepared by a simple synthetic strategy using solvothermal crystallization of titanium precursor on preformed Fe3O4 nanopartiles. The photo-degradation reaction of neutral red aqueous solution was tested to evaluate the visible-light photocatalytic activity of the as prepared Fe3O4@TiO2 nanoparticles, which show excellent photocatalytic activity compared with commercial P25 catalyst. Moreover, the Fe3O4@TiO2 nanocomposites can be easily separated from the reaction mixture, and maintain favorable photocatalytic activity after five cycles. The high visible light absorption of the Fe3O4@TiO2 nanocomposites may originate from the absence of electronic heterojunction, excellently dispersity and the high specific surface area of the as-synthesized Fe3O4@TiO2 samples

Facile Synthesis of CeO2-LaFeO3 Perovskite Composite and Its Application for 4-(Methylnitrosamino)-1-(3-Pyridyl)-1-Butanone (NNK) Degradation

A facile and environmentally friendly surface-ion adsorption method using CeCO3OH@C as template was demonstrated to synthesize CeO2-LaFeO3 perovskite composite material. The obtained composite was characterized by X-ray diffraction (XRD), fourier transform infrared spectra (FT-IR), field-emission scanning electron microscopy (FE-SEM), transmission electron microscopy (TEM), thermo-gravimetric analysis and differential scanning calorimetry (TG-DSC), N2 adsorption/desorption isotherms and X-ray photoelectron spectra (XPS) measurements. The catalytic degradation of nitrosamine 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) was tested to evaluate catalytic activity of the CeO2-LaFeO3 composite. Much better activity was observed for the CeO2-LaFeO3 composite comparing with CeO2 and LaFeO3. These results suggested that perovskite composite materials are a promising candidate for the degradation of tobacco-specific nitrosamines (TSNAs)