Memristive logic‐in‐memory (LIM) is an attractive candidate for in‐memory computing and thus would overcome some of the issues concerning the von Neumann bottleneck, which has been intensively investigated. Here, a multi‐bit and functionally complete LIM strategy is designed to efficiently perform multi logical functions in parallel. This strategy is experimentally demonstrated by a multi‐bit ferroelectric tunnel junction (FTJ) memristor with a sub‐nanosecond operation speed which is nearly two orders of magnitude faster than the previous memristive LIM. Using the four resistance states (2‐bit) of only a single FTJ memristor cell, two logical computations are successfully performed in parallel, and the 16 complete Boolean logic functions are implemented within only two steps. In addition, the multi‐encoding schemes are proposed to further improve the efficiency and flexibility of parallel logical computations. Accordingly, the 1‐bit binary full adder can be implemented using as less as three parallel memristors by only performing five steps, and on this basis the N‐bit full adder can also be realized. These results provide a highly efficient LIM approach, which could be a promising candidate for future computing architecture.

Sepsis, a serious inflammatory response that can be fatal, has a poorly understood pathophysiology. The Metabolic syndrome (MetS), however, is associated with many cardiometabolic risk factors, many of which are highly prevalent in adults. It has been suggested that Sepsis may be associated with MetS in several studies. Therefore, this study investigated diagnostic genes and metabolic pathways associated with both diseases. In addition to microarray data for Sepsis, PBMC single cell RNA sequencing data for Sepsis and microarray data for MetS were downloaded from the GEO database. Limma differential analysis identified 122 upregulated genes and 90 downregulated genes in Sepsis and MetS. WGCNA identified brown co-expression modules as Sepsis and MetS core modules. Two machine learning algorithms, RF and LASSO, were used to screen seven candidate genes, namely, STOM, BATF, CASP4, MAP3K14, MT1F, CFLAR and UROD, all with an AUC greater than 0.9. XGBoost assessed the co-diagnostic efficacy of Hub genes in Sepsis and MetS. The immune infiltration results show that Hub genes were expressed at high levels in all immune cells. After performing Seurat analysis on PBMC from normal and Sepsis patients, six immune subpopulations were identified. The metabolic pathways of each cell were scored and visualized using ssGSEA, and the results show that CFLAR plays an important role in the glycolytic pathway. Our study identified seven Hub genes that serve as co-diagnostic markers for Sepsis and MetS and revealed that diagnostic genes play an important role in immune cell metabolic pathway.

To reduce the cost of designing new specialized FPGA boards as direct-summation MOND (Modified Newtonian Dynamics) simulator, we propose a new heterogeneous architecture with existing FPGA boards, which is called RP-ring (reconfigurable processor ring). This design can be expanded conveniently with any available FPGA board and only requires quite low communication bandwidth between FPGA boards. The communication protocol is simple and can be implemented with limited hardware/software resources. In order to avoid overall performance loss caused by the slowest board, we build a mathematical model to decompose workload among FPGAs. The dividing of workload is based on the logic resource, memory access bandwidth, and communication bandwidth of each FPGA chip. Our accelerator can achieve two orders of magnitude speedup compared with CPU implementation.

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