Sandslash: A Two-Level Framework for Efficient Graph Pattern Mining

TL;DR

Sandslash introduces a two-level graph pattern mining framework that balances productivity and efficiency, outperforming existing systems and expert implementations through automatic and manual optimizations.

Contribution

It presents a novel in-memory GPM framework with a high-level API for ease of use and a low-level API for performance tuning, enabling flexible, efficient large-scale graph pattern mining.

Findings

Outperforms state-of-the-art GPM systems by up to 13.8x

Achieves 2.3x better performance than expert-optimized implementations

Supports both high productivity and high efficiency in GPM applications

Abstract

Graph pattern mining (GPM) is used in diverse application areas including social network analysis, bioinformatics, and chemical engineering. Existing GPM frameworks either provide high-level interfaces for productivity at the cost of expressiveness or provide low-level interfaces that can express a wide variety of GPM algorithms at the cost of increased programming complexity. Moreover, existing systems lack the flexibility to explore combinations of optimizations to achieve performance competitive with hand-optimized applications. We present Sandslash, an in-memory Graph Pattern Mining (GPM) framework that uses a novel programming interface to support productive, expressive, and efficient GPM on large graphs. Sandslash provides a high-level API that needs only a specification of the GPM problem, and it implements fast subgraph enumeration, provides efficient data structures, and applies high-level optimizations automatically. To achieve performance competitive with expert-optimized implementations, Sandslash also provides a low-level API that allows users to express algorithm-specific optimizations. This enables Sandslash to support both high-productivity and high-efficiency without losing expressiveness. We evaluate Sandslash on shared-memory machines using five GPM applications and a wide range of large real-world graphs. Experimental results demonstrate that applications written using Sandslash high-level or low-level API outperforms state-of-the-art GPM systems AutoMine, Pangolin, and Peregrine on average by 13.8x, 7.9x, and 5.4x, respectively. We also show that these Sandslash applications outperform expert-optimized GPM implementations by 2.3x on average with less programming effort.