Checkpointing is essential for fault tolerance in large-scale LLM training, yet periodic full-state checkpoints bring heavy I/O overhead and training stalls. Prior work suggests that differential checkpointing is ineffective for LLMs, since most parameters updates every iteration, leading to dense updates. This paper revisit this assumption and observe that parameter updates are naturally generated inside optimizer execution and exhibit significant temporal and layer-wise heterogeneity. Guided by this, we present wdCP, a lightweight runtime that captures optimizer-level parameter deltas and asynchronously persists them using a windowed buffering mechanism. wdCP further introduces lightweight anchor snapshots to bound recovery cost. We implement wdCP and evaluate it on several representative models. Results show that wdCP introduces less than 5% training overhead while achieving up to 69.2× reduction in checkpoint size and enabling fast, bounded recovery.

Pavlovian associative memory plays an important role in our daily life and work. The realization of Pavlovian associative memory at the deoxyribonucleic acid (DNA) molecular level will promote the development of biological computing and broaden the application scenarios of neural networks. In this article, bionic associative memory and temporal order memory circuits are constructed by DNA strand displacement (DSD) reactions. First, a temporal logic gate is constructed on the basis of DSD circuit and extended to a three-input temporal logic gate. The output of temporal logic gate is used for the weight species of associative memory. Second, the forgetting module and output module based on the DSD circuit are constructed to realize some functions of associative memory, including associative memory with simultaneous stimulus, associative memory with interstimulus interval effect, and the facilitation by intermittent stimulus. In addition, the coding, storage, and retrieval modules are designed based on the analysis and memory capabilities of temporal logic gate for temporal information. The temporal order memory circuit is constructed, demonstrating the temporal order memory ability of DNA circuit. Finally, the reliability of the circuit is verified through Visual DSD software simulation. Our work provides ideas and inspiration to construct more complex DNA bionic circuits and intelligent circuits by using DSD technology.

Performance measurement is essential for detecting potential performance issues and guiding optimization efforts. However, acquiring I/O traces of real applications can be costly in production environments. Also, existing performance measurement tools, such as FIO and Iometer, often oversimplify real-world application characteristics. In this paper, we introduce TraceGen, a block-level performance measurement tool for storage systems that consists of a trace analyzer and a trace generator. The trace analyzer produces two categories of traces: (i) new traces with specified characteristics designed to accurately simulate a range of applications, and (ii) extended traces that maintain similar workload characteristics to the input traces, thereby improving measurement accuracy during trace replay. We evaluate TraceGen using traces from an enterprise production environment and demonstrate its capability to generate new traces with an error margin of less than 1%.

As network techniques rapidly evolve, attacks are becoming increasingly sophisticated and threatening. Network intrusion detection has been widely accepted as an effective method to deal with network threats. Many approaches have been proposed, exploring different techniques and targeting different types of traffic. Anomaly-based network intrusion detection is an important research and development direction of intrusion detection. Despite the extensive investigation of anomaly-based network intrusion detection techniques, there lacks a systematic literature review of recent techniques and datasets. We follow the methodology of systematic literature review to survey and study 119 top-cited papers on anomaly-based intrusion detection. Our study rigorously and comprehensively investigates the technical landscape of the field in order to facilitate subsequent research within this field. Specifically, our investigation is conducted from the following perspectives: application domains, data preprocessing and attack-detection techniques, evaluation metrics, coauthor relationships, and datasets. Based on the research results, we identify unsolved research challenges and unstudied research topics from each perspective, respectively. Finally, we present several promising high-impact future research directions.

A new multiconstrained routing algorithm based on quality of Service (QoS), DAG_DMCOP, is proposed. The algorithm is divided into two parts: (1) Pruning strategy. Find all paths that meet the needs of multiple constraints and convert the network topology into a Directed Acyclic Graph (DAG). (2) Search strategy. The link synthesis cost function is introduced to adjust the multiconstrained conditions (bandwidth, delay, delay jitter and other QoS parameters) adaptively. Then an improved Dijkstra algorithm is used to find out the optimal path that meets the needs of multiple constraints. Simulation show the algorithm can quickly find the path with the least cost and is suitable for large-scale multiconstrained routing networks. It is an efficient new algorithm for solving multiconstrained routing problems.