Sunder: Enabling Low-Overhead and Scalable Near-Data Pattern Matching Acceleration

ABSTRACT Automata processing is an efficient computation model for regular expressions and other forms of sophisticated pattern matching. The demand for high-throughput and real-time pattern matching in many applications, including network intrusion detection and spam filters, has motivated several in-memory architectures for automata processing. Existing in-memory architectures focus on accelerating the pattern-matching kernel, but either fail to support a practical reporting solution or optimistically assume that the reporting stage is not the performance bottleneck. However, gathering and processing the reports can be the major bottleneck, especially when the reporting frequency is high. Moreover, all the existing in-memory architectures work with a fixed processing rate (mostly 8-bit/cycle), and they do not adjust the input consumption rate based on the properties of the applications, which can lead to throughput and capacity loss. To address these issues, we present Sunder, an in-SRAM pattern matching architecture, to processes a reconfigurable number of nibbles (4-bit symbols) in parallel, instead of fixed-rate processing, by adopting an algorithm/architecture methodology to perform hardware-aware transformations. Inspired by prior work, we transform the commonly-used 8-bit processing to nibble-processing (4-bit processing) to reduce hardware requirements exponentially and achieve higher information density. This frees up space for storing reporting data in place, which significantly eliminates host communication and reporting overhead. Our proposed reporting architecture supports in-place report summarization and provides an easy access mechanism to read the reporting data. As a result, Sunder enables a low-overhead, high-performance, and flexible in-memory pattern-matching and reporting solution. Our results confirm that Sunder reporting architecture has zero performance overhead for 95% of the applications and incurs only 2% additional hardware overhead.