NPS: A Framework for Accurate Program Sampling Using Graph Neural Network

With the end of Moore's Law, there is a growing demand for rapid architectural innovations in modern processors, such as RISC-V custom extensions, to continue performance scaling. Program sampling is a crucial step in microprocessor design, as it selects representative simulation points for workload simulation. While SimPoint has been the de-facto approach for decades, its limited expressiveness with Basic Block Vector (BBV) requires time-consuming human tuning, often taking months, which impedes fast innovation and agile hardware development. This paper introduces Neural Program Sampling (NPS), a novel framework that learns execution embeddings using dynamic snapshots of a Graph Neural Network. NPS deploys AssemblyNet for embedding generation, leveraging an application's code structures and runtime states. AssemblyNet serves as NPS's graph model and neural architecture, capturing a program's behavior in aspects such as data computation, code path, and data flow. AssemblyNet is trained with a data prefetch task that predicts consecutive memory addresses. In the experiments, NPS outperforms SimPoint by up to 63%, reducing the average error by 38%. Additionally, NPS demonstrates strong robustness with increased accuracy, reducing the expensive accuracy tuning overhead. Furthermore, NPS shows higher accuracy and generality than the state-of-the-art GNN approach in code behavior learning, enabling the generation of high-quality execution embeddings

Comparison and Selection of Data Processing Methods for the Application of Cr3+ Photoluminescence Piezospectroscopy to Thermal Barrier Coatings

Thermal barrier coatings (TBCs) are an indispensable part of the blades used in aeroengines. Under a high-temperature service environment, the thermal oxidation stress at the interface is the main cause of thermal barrier failure. Cr3+ photoluminescence piezospectroscopy has been successfully used to analyze the thermal oxidation stress of TBCs, but systematic and quantitative analysis results for use in data processing are still lacking, especially with respect to the identification of peak positions. The processing methods used to fit spectral data were studied in this work to accurately characterize TBC thermal oxidation stress using Cr3+ photoluminescence spectroscopy. Both physical and numerical experiments were carried out, where Cr3+ photoluminescence spectra were detected from alumina ceramic samples under step-by-step uniaxial loading, and the simulated spectra were numerically deduced from the measured spectral data. Then, the peak shifts were obtained by fitting all spectral data by using Lorentzian, Gaussian and Psd-Voigt functions. By comparing the fitting results and then discussing the generation mechanism, the Lorentzian function—not the Psd-Voigt function that is most widely utilized—was regarded as the most applicable method for the application of Cr3+ photoluminescence piezospectroscopy to TBCs because of its sufficient sensitivity, stability and confidence for quantitative stress analysis

Measurement of Stress Optic Coefficient for Thermal Barrier Coating Based on Terahertz Time-Domain Spectrum

The residual stress introduced inside the thermal barrier coating (TBC) top coating during manufacturing and service processes is one of the main causes of thermal barrier failure. Therefore, a nondestructive and accurate measurement of the residual stress in top coating is essential for the evaluation of TBC life. The terahertz time-domain spectroscopy (THz-TDS) technique, which is based on the calibration or measurement of the stress optical coefficients of the measured materials, is applicable to the measuring of internal stress of nonmetal materials. In this work, to characterize the internal stress in TBC, the stress optic coefficient of the TBC top coating was measured by reflection-type THz-TDS. First, the mechanics model for the internal stress measurement in a TBC top coating was derived based on the photoelastic theory. Then, the THz time-domain spectra of TBC specimens under different loadings were measured in situ by a reflection-type THz-TDS system. Finally, the unimodal fitting, multimodal fitting and barycenter methods were used to carry out the data processing of the THz time-domain spectral-characteristic peaks. By comparing the processed results, the results using the barycenter method were regarded as the calibrated stress optical coefficient of the TBC due to the method’s sufficient accuracy and stability

Assessment of the Adverse Health Effects of Aflatoxin Exposure from Unpackaged Peanut Oil in Guangdong, China

Aflatoxins are liver carcinogens and are common contaminants in unpackaged peanut (UPP) oil. However, the health risks associated with consuming aflatoxins in UPP oil remain unclear. In this study, aflatoxin contamination in 143 UPP oil samples from Guangdong Province were assessed via liquid chromatography–tandem mass spectrometry (LC-MS). We also recruited 168 human subjects, who consumed this oil, to measure their liver functions and lipid metabolism status. Aflatoxin B1 (AFB1) was detected in 79.72% of the UPP oil samples, with levels ranging from 0.02 to 174.13 μg/kg. The average daily human intake of AFB1 from UPP oil was 3.14 ng/kg·bw/day; therefore, the incidence of liver cancer, caused by intake of 1 ng/kg·bw/day AFB1, was estimated to be 5.32 cases out of every 100,000 persons per year. Meanwhile, Hepatitis B virus (HBV) infection and AFB1 exposure exerted a synergistic effect to cause liver dysfunction. In addition, the triglycerides (TG) abnormal rate was statistically significant when using AFB1 to estimate daily intake (EDI) quartile spacing grouping (p = 0.011). In conclusion, high aflatoxin exposure may exacerbate the harmful effects of HBV infection on liver function. Contamination of UPP oil with aflatoxins in Guangdong urgently requires more attention, and public health management of the consumer population is urgently required

Neural EGFL-Like 1 Is a Downstream Regulator of Runt-Related Transcription Factor 2 in Chondrogenic Differentiation and Maturation

Recent studies indicate that neural EGFL-like 1 (Nell-1), a secretive extracellular matrix molecule, is involved in chondrogenic differentiation. Herein, we demonstrated that Nell-1 serves as a key downstream target of runt-related transcription factor 2 (Runx2), a central regulator of chondrogenesis. Unlike in osteoblast lineage cells where Nell-1 and Runx2 demonstrate mutual regulation, further studies in chondrocytes revealed that Runx2 tightly regulates the expression of Nell-1; however, Nell-1 does not alter the expression of Runx2. More important, Nell-1 administration partially restored Runx2 deficiency induced impairment of chondrocyte differentiation and maturation in vitro, ex vivo, and in vivo. Mechanistically, although the expression of Nell-1 is highly reliant on Runx2, the prochondrogenic function of Nell-1 persisted in Runx2(-/-) scenarios. The biopotency of Nell-1 is independent of the nuclear import and DNA binding functions of Runx2 during chondrogenesis. Nell-1 is a key functional mediator of chondrogenesis, thus opening up new possibilities for the application of Nell-1 in cartilage regeneration.NIH-National Institute of Arthritis and Musculoskeletal and Skin Diseases grants [R01AR066782, R01AR068835, R01AR061399]; UCLA/NIH Clinical and Translational Science Institute (CTSI) grant [UL1TR000124]; National Aeronautical and Space Administration [GA-2014-154]; International S&T Cooperation Program of China grant [2013DFB30360]SCI(E)ARTICLE5963-97218