Skill UI

This guide outlines the necessary steps to ensure that parallel computing performance papers are scientifically reproducible. Since parallel results depend heavily on machine architecture, topology, and runtime conditions, proper documentation must cover everything from CPU/GPU specifications and interconnects to thread pinning policies, random seeds, and compiler flags. The focus is on proving the scaling trend, not just the absolute numbers, allowing results to hold true across different hardware platforms.

This comprehensive guide helps authors assess if their manuscript is a suitable fit for Proceedings of the IEEE. It details the journal's high standards, guiding the transformation of primary research into comprehensive, balanced, and forward-looking review, survey, or tutorial articles. Use this resource to understand the required scope, synthesis depth, and common pitfalls to avoid desk rejection.

This guide provides a comprehensive audit checklist for designing and evaluating sensor-based systems (SenSys). It mandates rigorous, real-world measurements across five core axes: energy efficiency, on-device latency distribution, ground truth accuracy, deployment realism, and embedded AI footprint. It ensures that research results are based on measured hardware performance, not simulations or idealized baselines.

A comprehensive guide for submitting networking research artifacts for SIGCOMM conferences. It dictates how to package code, downscale topologies, substitute traces, and pin environments so that reviewers can independently verify and reproduce the paper's headline results, establishing verifiable scientific claims.

A comprehensive guide for designing and auditing high-stakes networking experiments, particularly for top-tier academic submissions like SIGCOMM. It outlines the 'evidence ladder' from microbenchmarks to live deployment, emphasizing the need to select robust baselines, report full performance distributions (percentiles and variance), and accurately map the mechanism's operational break points.

This guide provides comprehensive best practices for designing and auditing cloud system evaluations, particularly for academic submissions. It mandates that claims must be supported by measured evidence from real or realistic deployments, moving beyond simple simulations. Key metrics emphasized include tail latency (p99), operational cost modeling, and verifiable behavior under scale and multi-tenancy.

This guide assists researchers in determining the optimal venue for their formal verification project. It helps decide whether the work belongs at TACAS (ETAPS) or a sibling conference (like CAV or VMCAI), depending on the emphasis (tool vs. theory), and guides the selection among the four distinct contribution categories (Research, Tool, Case-study, Demonstration).

This comprehensive guide is designed for authors submitting manuscripts in water science or engineering. It details the high standards, scope, and expected rigor for the flagship journal, Water Research. It covers the necessary depth of mechanistic or methodological advances, strict experimental design requirements (including mass balances and controls), and the IMRaD structure required for publication.