Process variation has become prominent in the advanced CMOS technology, making the timing of fabricated circuits more uncertain. In this paper, we propose a Layout-Aware Path Selection (LAPS) technique to accurately estimate the circuit timing variation from a small set of paths. Three features of paths are considered during the path selection. Experiments conducted on benchmark circuits with process variation simulated with VARIUS show that, by selecting only hundreds of paths, the fitting errors of timing distribution are kept below 5.3% when both spatial correlated and spatial uncorrelated process variations exist.

The Linux kernel has been applied in various security-sensitive fields, so ensuring its security is crucial. Vulnerabilities in the Linux kernel are usually caused by undefined behaviors of the C programming language, the most threatening of which are memory safety vulnerabilities. Both the software-based and hardware approaches to memory safety have disadvantages of poor performance, false positives, and poor compatibility. This paper explores the feasibility of using the safe programming language Rust to reconstruct a Linux kernel component and open-source the component's code. We leverage the Rust FFI mechanism to design a safe foreign interface layer to enable the reconstructed component to invoke other Linux functionalities, and then use Rust to reconstruct the component, during which we leverage Rust's type-safety and ownership mechanisms to improve its security, and finally export the C interface of the component to enable the invocation by the Linux kernel. The performance and memory overhead of the reconstructed component, referred to as “rOOM”, were evaluated, revealing a performance overhead of 8.9% in kernel mode, 5% in user mode, 3% in real time, and a memory overhead of 0.06%. These results suggest that it is possible to develop key components of the Linux kernel using Rust in terms of functionality, performance, and memory overhead.

In this letter, a deep neural network (DNN) aided joint source-channel (JSCC) decoding scheme is proposed for polar codes. In the proposed scheme, an integrated factor graph with an unfolded structure is first designed. Then a DNN aided flooding belief propagation decoding (FBP) algorithm is proposed based on the integrated factor, in which both source and channel scaling parameters in the BP decoding are optimized for better performance. Experimental results show that, with the proposed DNN aided FBP decoder, the polar coded JSCC scheme can have about 2-2.5 dB gain over different source statistics p with source message length NSC = 128 and 0.2-1 dB gain over different source statistics p with source message length NSC = 512 over the polar coded JSCC system with existing BP decoder.