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Sanjog Sigdel

Publications and source records attributed to Sanjog Sigdel.

3 recordsLinked to original sources

A Bounded Reclaim Actuator for PSI-Guided Compressed Memory: A Controlled Ablation

When the aggregate working set of active processes exceeds physical RAM capacity, the machine experiences memory pressure. Applications may therefore slow down before the kernel kills a process. Linux provides several ways to observe and respond: Pressure Stall Information (PSI) can detect memory-related task stalls, zram can provide compressed in-memory swap space, and cgroup v2 can request memory reclamation within a selected control group. These facilities are often discussed together even though they act at different points in the pressure path. This paper examines that distinction with a controlled systems study. We compare three setups: zram enabled from startup; zram enabled only after PSI indicates memory pressure; and zram enabled from startup with a one-time 96 MiB cgroup reclaim request. We first selected the request size in a 16-case pilot, then ran 180 confirmatory cases, 60 cases for each setup, on nine 1-vCPU Linux virtual machines with compute and SQLite workloads. Compared with static zram, the bounded reclaim configuration reduced compute p99 response time by 6\%, while the SQLite result was statistically indistinguishable. Delayed activation had higher median p99 latency than both alternatives. These results suggest that the benefit depends on the foreground workload and its memory-access path, rather than a general improvement across workloads.

cs.OS

An Artificial Intelligence Driven Semantic Similarity-Based Pipeline for Rapid Literature

We propose an automated pipeline for performing literature reviews using semantic similarity. Unlike traditional systematic review systems or optimization based methods, this work emphasizes minimal overhead and high relevance by using transformer based embeddings and cosine similarity. By providing a paper title and abstract, it generates relevant keywords, fetches relevant papers from open access repository, and ranks them based on their semantic closeness to the input. Three embedding models were evaluated. A statistical thresholding approach is then applied to filter relevant papers, enabling an effective literature review pipeline. Despite the absence of heuristic feedback or ground truth relevance labels, the proposed system shows promise as a scalable and practical tool for preliminary research and exploratory analysis.

cs.AI

A Study Of Sudoku Solving Algorithms: Backtracking and Heuristic

This paper presents a comparative analysis of Sudoku-solving strategies, focusing on recursive backtracking and a heuristic-based constraint propagation method. Using a dataset of 500 puzzles across five difficulty levels (Beginner to Expert), we evaluated performance based on average solving time. The heuristic approach consistently outperformed backtracking, achieving speedup ratios ranging from 1.27x in Beginner puzzles to 2.91x in Expert puzzles. These findings underscore the effectiveness of heuristic strategies, particularly in tackling complex puzzles across varying difficulty levels.

cs.LO