Skill UI

This guide provides expert advice on positioning research papers for top-tier computer architecture conferences (e.g., ISCA, MICRO, ASPLOS). It teaches authors how to identify the 'center-of-gravity' of their novelty—whether it lies in the hardware organization, the hardware/software contract, or the software layer alone—to maximize review acceptance chances and successfully navigate the competitive academic publication landscape.

A comprehensive guide designed to help researchers determine the optimal top-tier conference venue for their computer architecture work. It provides detailed criteria—such as mechanism-residency tests, hardware cost analysis, and scope boundaries—to guide authors in correctly placing their research between venues like MICRO, ISCA, ASPLOS, and DAC.

Provides comprehensive guidelines for achieving high reproducibility in Machine Learning Systems (MLSys) performance claims. It details how to rigorously control sources of non-determinism (e.g., thermal noise, random seeds) and pin the entire technical stack—from hardware and drivers to frameworks and serving policies—to ensure results can be validated by third parties.

This guide details the rigorous process for packaging research artifacts in mobile communications for academic evaluation committees (AEC). It emphasizes creating a hardware-optional path, defining claims (badges), and ensuring reproducibility through smoke runs, recorded replay paths, and permanent DOI-backed archiving, allowing evaluation even without specialized lab equipment.

A comprehensive guide to ensuring reproducibility in radio frequency (RF) physical layer measurements. It details the necessity of maintaining a detailed provenance ledger—recording radio hardware, channel conditions, mobility patterns, and software versions at the time of the run. The goal is not bit-identical results, but documenting variance and methodology so that findings can be validated on different testbeds or later in time, while also addressing legal and ethical data shipping constraints.

A comprehensive guide for submitting research artifacts to the MobiSys Artifact Evaluation Committee (AEC). It details the process for achieving three independent ACM badges (Available, Functional, Results Reproduced). Emphasis is placed on creating fully reproducible, script-first workflows, designing for hardware-optional environments, and maintaining strict anonymity during review.

Provides a rigorous framework for ensuring the reproducibility of systems research presented at conferences like OSDI. It mandates maintaining a comprehensive, machine-readable provenance ledger that records hardware specifications, software dependencies, workload traces, and measurement policies throughout the entire experimental lifecycle, preventing 'artifact drift' and ensuring verifiable results.

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 guide helps researchers determine the correct academic venue for their work in parallel and concurrent computing. It clarifies the scope of PPoPP versus related conferences (CGO, PLDI, ASPLOS, HPCA, POPL, etc.) by asking: 'Is the parallelism the point, or is it the setting?' Use this framework to distinguish contributions focused on parallel algorithms, compiler optimization, concurrency theory, or hardware microarchitecture.

This guide provides a comprehensive project management framework for submitting research to major robotics conferences, particularly RSS. It maps out the complex annual cycle, from abstract submission to final presentation, detailing critical deadlines, required milestones (like hardware trials and writing drafts), and fallback options at sibling venues (IROS, CoRL, ICRA). Essential for researchers managing time-sensitive academic pipelines.

This guide details the process of achieving ACM badges (Available, Functional, Reproduced) for academic artifacts at SenSys. It emphasizes creating a hardware-optional evaluation path, allowing reviewers to verify results and functionality without access to the original testbed. Key steps include implementing graded replay tiers, documenting data provenance (energy, traces), and performing smoke-runs.

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.