Resilient neural network training for accelerators with computing errors

—With the advancements of neural networks, customized accelerators are increasingly adopted in massive AI applications. To gain higher energy efficiency or performance, many hardware design optimizations such as near-threshold logic or overclocking can be utilized. In these cases, computing errors may happen and the computing errors are difficult to be captured by conventional training on general purposed processors (GPPs). Applying the offline trained neural network models to the accelerators with errors directly may lead to considerable prediction accuracy loss. To address this problem, we explore the resilience of neural network models and relax the accelerator design constraints to enable aggressive design options. First of all, we propose to train the neural network models using the accelerators’ forward computing results such that the models can learn both the data and the computing errors. In addition, we observe that some of the neural network layers are more sensitive to the computing errors. With this observation, we schedule the most sensitive layer to the attached GPP to reduce the negative influence of the computing errors. According to the experiments, the neural network models obtained from the proposed training outperform the original models significantly when the CNN accelerators are affected by computing errors

Demonstration of Adiabatic Variational Quantum Computing with a Superconducting Quantum Coprocessor

Adiabatic quantum computing enables the preparation of many-body ground states. This is key for applications in chemistry, materials science, and beyond. Realisation poses major experimental challenges: Direct analog implementation requires complex Hamiltonian engineering, while the digitised version needs deep quantum gate circuits. To bypass these obstacles, we suggest an adiabatic variational hybrid algorithm, which employs short quantum circuits and provides a systematic quantum adiabatic optimisation of the circuit parameters. The quantum adiabatic theorem promises not only the ground state but also that the excited eigenstates can be found. We report the first experimental demonstration that many-body eigenstates can be efficiently prepared by an adiabatic variational algorithm assisted with a multi-qubit superconducting coprocessor. We track the real-time evolution of the ground and exited states of transverse-field Ising spins with a fidelity up that can reach about 99%.Comment: 12 pages, 4 figure

Factors underlying differences in knowledge, explicit stigma and implicit biases towards autism across Hong Kong, the United Kingdom and the United States

A growing literature suggests that there is cross-cultural variation in levels of autism-related stigma, which may partially be explained by differences in cultural orientation or autism-related knowledge between countries. This literature has relied heavily on self-report measures of explicit attitudes towards autism; little research has examined implicit biases, and whether these implicit biases vary across cultures. Thus, here we had two aims: (1) to assess the contribution of knowledge and cultural orientation to both explicit stigma and implicit biases, and (2) to compare autism-related knowledge, explicit stigma, and implicit biases across university students in Hong Kong (n = 119), the United Kingdom (n = 120), and the United States (n = 122). Replicating prior work, we found that explicit stigma was predicted by less accurate knowledge, lower horizontal collectivism, greater vertical individualism, and higher implicit biases. Implicit biases were directly predicted by age and explicit stigma, and indirectly predicted by vertical individualism (positively) and horizontal collectivism (negatively) via explicit stigma. Knowledge and explicit stigma differed across countries, even after accounting for covariates: students in Hong Kong displayed less accurate knowledge, and higher explicit stigma towards autism, than those in the United Kingdom and United States. However, implicit biases did not differ between countries

A Novel Collagen Extraction Method Based on Microwave Irradiation

Content: Microwave was used as a thermal source to extract collagen acid from the cattle hide in the present work. The effects of microwave on collagen extraction yields were studied under different microwave temperatures, time and hide-liquid ratio. The optimal extraction process was obtained by an orthogonal experiment, and the composition, structure and properties of the extracted collagen were characterized by amino acid analysis, SDS-PAGE, FTIR, UV-Vis, CD, FL, and VP-DSC. The results showed that the extraction rate of collagen was positively correlated with temperature, time and hide-liquid ratio. Under the condition of 35 °C, 6 h and 1:30 of solid-liquid ratio, the extraction proportion of collagen extracted under microwave was the highest, reaching to 13.40 %. The extracted collagen was identified as type I collagen by Amino acid analysis, and the graphic pattern of SDS-PAGE, FTIR and UV-Vis showed that the extracted collagen was similar to the standard type I collagen. Also, the results suggest that the triple helical structure exists still in the extracted collagen. The transition from triple helix to random coil of the extracted collagen was 41 ℃. These results provide a scientific basis for microwave technology for the extraction of collagen. Take-Away: The results showed that the extraction rate of collagen was positively correlated with temperature, time and hide-liquid ratio. Under the condition of 35 °C, 6 h and 1:30 of solid-liquid ratio, the extraction proportion of collagen extracted under microwave was the highest, reaching to 13.40 %. The extracted collagen was identified as type I collagen by Amino acid analysis, and the graphic pattern of SDS-PAGE, FTIR and UV-Vis showed that the extracted collagen was similar to the standard type I collagen. Also, the results suggest that the triple helical structure exists still in the extracted collagen. The transition from triple helix to random coil of the extracted collagen was 41 ℃. These results provide a scientific basis for microwave technology for the extraction of collagen

Tris(tetra­methyl­ammonium) tetra-μ2-sulfido-tetra­sulfidocopper(I)dimolyb­denum(VI) N,N-dimethyl­formamide solvate

The title compound, (C4H12N)3[CuMo2S8]·C3H7NO, was obtained from the self-assembly of tetra­thio­molybdate, tetra­methyl­ammonium nitrate and cuprous sulfide in dimethyl­formamide (DMF). The asymmetric unit contains three (NMe4)+ cations, one [Mo2S8Cu]3− anion and one DMF solvent mol­ecule, and no obvious inter­actions are observed between these species. The trinuclear anion can be viewed as fused [MoS4Cu]− units sharing a copper center. The geometric parameters of the trivalent anion are comparable to those reported for other related salts including isomorphous anions, namely (NEt4)2(PPh4)[Mo2S8Cu] (a) and (Ph3P=N=PPh3)2(NEt4)[W2S8Cu]·2CH3CN (b). However, the Mo—Cu—Mo angle is found to be 160.24 (3)° for the title salt, while this angle is 162.97 (2)° in (a) and the W—Cu—W angle is 170.3 (2)° in (b), indicating that the largest deviation from linearity is in the title compound