A Coarse-Grained Reconfigurable Architecture with a Fault Tolerant Non-Volatile Configurable Memory

Abstract

Recent IoT devices require extremely low standby power consumption, while a certain performance is needed during the active time, and Coarse Grain Reconfigurable Arrays (CGRAs) are suitable because of their high energy efficiency. However, even in CGRAs, the leakage power for its configuration memory must be reduced. Although the power gating is a popular technique, the data in flip-flops and memory are lost so they must be retrieved after the wake-up. Recovering everything requires numerous state transitions and considerable overhead both on its execution time and energy. To address the problem, Non-volatile Cool Mega Array (NVCMA), a CGRA providing non-volatile flip-flops (NVFFs) with spin transfer torque type non-volatile memory (NVM) technology has been developed. However, in general, non-volatile memory technologies have problems with reliability. Some NVFFs are stacked-at-0/1, and cannot store the data in a certain possibility. To improve the chip yield, we propose a mapping algorithm to avoid faulty processing elements of the CGRA caused by the erroneous configuration data. Then, we also propose a method to add an error-correcting code (ECC) mechanism to NVFFs used for the configuration and constant memory. The proposed method was applied to NVCMA to evaluate the availability rate and reduction of write time. By using both methods, the 99.4% availability ratio is achieved with 0.1% probability of faulty FFs, while almost no chips are available without using them. The energy for storing data becomes about 2.28 times because of the hardware overhead of ECC but the proposed method can save 11.1% of the storing energy on average.