Endurance-Aware RRAM-Based Reconfigurable Architecture using TCAM Arrays

Field-Programmable Gate Arrays (FPGAs) have enabled the acceleration of important applications in the networking, cloud, and artificial intelligence domains, while providing a flexible fabric that can be reprogrammed on demand. Still, the high static power dissipation of FPGAs driven by Static Random Access Memories (SRAMs) leads them to energy consumption levels that may be unacceptable for several application domains. Reconfigurable fabrics with emerging Resistive RAM (RRAM) technologies have been considered as one of the most promising solutions to address these energy issues of current FPGAs. However, the low endurance and the high variability of these emerging devices present a threat to the demands for reconfiguration cycles of current applications, pushing for novel architectures and design strategies techniques for improving the device's lifetime. To address these challenges, we propose a novel reconfigurable architecture targeting classes of applications that require high flexibility in the field. More specifically, we introduce a reconfigurable architecture based on Ternary Content-Addressable Memories (TCAMs) that meets a double mission: to accelerate and tolerate endurance and variation issues supported by a CAD tool that foresees the reuse of data configuration, allowing for an increased endurance in the field. We present the potential of the proposed architecture and its synthesis flow for processing Regular Expression Matching (REM), widely used in network intrusion detection systems. The results show that the performance can achieve up to 32Gbps throughput at 0.89W, while improving the device's lifetime by two orders of magnitude.