Data persistence is necessary for many in-memory applications. However, the disk-based data persistence largely slows down in-memory applications. Emerging non-volatile memory (NVM) offers an opportunity to achieve in-memory data persistence at the DRAM-level performance. Nevertheless, NVM typically requires a software library to operate NVM data, which brings significant overhead. This article demonstrates that a hardware-based high-frequency checkpointing mechanism can be used to achieve efficient in-memory data persistence on NVM. To maintain checkpoint consistency, traditional logging and copy-on-write techniques incur excessive NVM writes that impair both performance and endurance of NVM; recent work attempts to solve the issue but requires a large amount of metadata in the memory controller. Hence, we design a new dual-page checkpointing system, which achieves low metadata cost and eliminates most excessive NVM writes at the same time. It breaks the traditional trade-off between metadata space cost and extra data writes. Our solution outperforms the state-of-the-art NVM software libraries by 13.6× in throughput, and leads to 34% less NVM wear-out and 1.28× higher throughput than state-of-the-art hardware checkpointing solutions, according to our evaluation with OLTP, graph computing, and machine-learning workloads.

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A new modified model based on the non-parallel primary shear zone is presented in this paper. Experiments showed that the primary shear zone in cutting process wasn’t an absolutely parallel-sided zone. In fact, there are small inclined angles in the primary shear zone. Therefore, in this paper, a correction coefficient is proposed to predict cutting forces exactly. The coordinate mapping approach is adopted to obtain the correction coefficient and the software MATLAB is utilized to predict cutting forces. The material of stainless steel 316L is used to validate the modified model. By comparison between predicted analysis and experimental results, the proposed model shows good agreements with experiments.

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With the development of the society, the improvement of people’s living standards, countless underground parking lots seem to be difficult to park and find cars. Underground parking lot was built under the thick concrete. Because the underground parking lot is built under the thick steel and cement, the GPS satellite signal can not penetrate the thick bunker, which leads to the problem that the navigation accuracy in the building is too low to be able to locate accurately. In order to solve this problem which is put forward an intelligent underground parking guidance system based on the wifi, the system install wifi routers on the underground parking lot, and mobile phones own wifi module scan wifi hotspots around the information, and then match the cloud database tagged wifi hotspots information, and get wifi hot spot on the map coordinate information. According to the mobile phone access to the location of the WIFI hotspot intensity information, the system gets to the phone’s current location information, and the coordinates of the map is updated. Fianlly, according to the system for the whole test, the test results show that the system has achieve the expected goals, and the operation is convenient, has certain market practical value.