Tools and Algorithms for SoC Communication Traces

TL;DR

This paper evaluates seven trace analysis techniques on communication-centric SoC traces, addressing challenges of large size and concurrency, and provides guidance on tool selection with performance benchmarks on synthetic and realistic traces.

Contribution

It offers a comprehensive comparison of existing trace analysis tools for SoC communication traces, including performance evaluation and a benchmark dataset.

Findings

Tools vary in effectiveness depending on trace characteristics.

Synthetic and real traces show different performance profiles.

Benchmark dataset aids future research in SoC trace analysis.

Abstract

In this paper, we study seven well-known trace analysis techniques both from the hardware and software domain and discuss their performance on communication-centric system-on-chip (SoC) traces. SoC traces are usually huge in size and concurrent in nature, therefore mining SoC traces poses additional challenges. We provide a hands-on discussion of the selected tools/algorithms in terms of the input, output, and analysis methods they employ. Hardware traces also varies in nature when observed in different level, this work can help developers/academicians to pick up the right techniques for their work. We take advantage of a synthetic trace generator to find the interestingness of the mined outcomes for each tool as well as we work with a realistic GEM5 set up to find the performance of these tools on more realistic SoC traces. Comprehensive analysis of the tool's performance and a benchmark trace dataset are also presented.