Iridescent: A Framework Enabling Online System Implementation Specialization

TL;DR

Iridescent is a framework that automates online system specialization by dynamically generating and testing different configurations guided by system performance metrics, improving performance adaptability.

Contribution

It introduces a novel framework for automated online system specialization that leverages runtime performance metrics to optimize configurations dynamically.

Findings

Feasibility demonstrated through implementation

Effective in improving system performance

Easy for developers to specify specialization space

Abstract

Specializing systems to specifics of the workload they serve and platform they are running on often significantly improves performance. However, specializing systems is difficult in practice because of compounding challenges: i) complexity for the developers to determine and implement optimal specialization; ii) inherent loss of generality of the resulting implementation, and iii) difficulty in identifying and implementing a single optimal specialized configuration for the messy reality of modern systems. To address this, we introduce Iridescent, a framework for automated online system specialization guided by observed overall system performance. Iridescent lets developers specify a space of possible specialization choices, and then at runtime generates and runs different specialization choices through JIT compilation as the system runs. By using overall system performance metrics to guide this search, developers can use Iridescent to find optimal system specializations for the hardware and workload conditions at a given time. We demonstrate feasibility, effectivity, and ease of use.