2DIO: A Cache-Accurate Storage Microbenchmark

2026-03-20

AI Summary

Existing storage microbenchmarking tools struggle to generate I/O traces that exhibit complex cache behaviors—such as performance cliffs and plateau effects—thereby limiting the evaluation and advancement of caching systems. This work proposes 2DIO, a novel approach that jointly models the short-term recency and long-term frequency characteristics of workloads through a compact ternary parameterization, enabling precise characterization of cache behavior. 2DIO innovatively constructs a portable and searchable parameter space that supports high-fidelity replay of real-world I/O traces under diverse replacement policies and facilitates the on-demand synthesis of traces spanning continuous “what-if” cache behaviors. Experimental results demonstrate that 2DIO achieves exceptional controllability, generality, and accuracy, significantly enhancing the flexibility and realism of cache system evaluation.

Technology Category

• Search and Optimization: Mixed Discrete/Continuous Search
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Knowledge Representation and Reasoning: Diagnosis and Abductive Reasoning

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• Security and Privacy: Large-scale security measurements
• Graph Algorithms and Modeling for the Web: Querying, indexing, and retrieval in Web-related graphs

Abstract

We introduce 2DIO, a microbenchmark creating cache-accurate, stressful I/O traces. While existing tools are limited to generating traces with well-behaved, concave hit ratio curves, 2DIO produces ones with tunable complex cache behaviors, particularly performance cliffs and plateaus. Our framework encodes a workload as a compact parameter triplet, capturing both short-term recency and long-term frequency. This parsimonious parameterization allows researchers to easily translate individual adjustments into predictable cache effects across various eviction policies, and enables the parameter space to be "swept" for exhaustive exploration of desired cache behavior, or to mimic real traces by calibrating parameters to match observed behaviors. The tuned parameters are portable, meaning if the scale of the system under evaluation changes, so too will the footprint and length of the trace, while the relative cache behaviors are preserved. Evaluations demonstrate 2DIO's ability to generate traces across a continuum of "what-if" cache behaviors and to reproduce real-world ones with high accuracy.

Problem

• cache behavior
• I/O trace
• microbenchmark
• hit ratio curve
• performance cliff

Innovation

• cache-accurate I/O traces
• parameterized workload modeling
• performance cliffs and plateaus
• portable trace generation
• microbenchmark