FELIX: Fast and Energy-Efficient Logic in Memory

The Internet of Things (IoT) has led to the emergence of big data. Processing this amount of data poses a challenge for current computing systems. PIM enables in-place computation which reduces data movement, a major latency bottleneck in conventional systems. In this paper, we propose an in-memory implementation of fast and energy-efficient logic (FELIX) which combines the functionality of PIM with memories. To the best of authors' knowledge, FELIX is the first PIM logic to enable the single cycle NOR, NOT, NAND, minority, and OR directly in crossbar memory. We exploit the voltage threshold-based memristors to enable single cycle operations. It is a purely in-memory execution which neither reads out data nor changes sense amplifiers, while preserving data in-memory. We extend these single cycle operations to implement more complex functions like XOR and addition in memory with 2× lower latency than the fastest published PIM technique. We also increase the amount of in-memory parallelism in our design by segmenting bitlines using switches. To evaluate the efficiency of our design at the system level, we design a FELIX-based HyperDimensional (HD) computing accelerator. Our evaluation shows that for all applications tested using HD, FELIX provides on average 128.8× speedup and 5,589.3× lower energy consumption as compared to AMD GPU. FELIX HD also achieves on average 2.21× higher energy efficiency, 1.86× speedup, and 1.68× less memory as compared to the fastest PIM technique.