论文标题
部分可观测时空混沌系统的无模型预测
Experimental demonstration of Single-Level and Multi-Level-Cell RRAM-based In-Memory Computing with up to 16 parallel operations
论文作者
论文摘要
电阻性记忆（RRAM）的横杆阵列具有实现内存计算（IMC）的承诺，但是由于设备不完美和设备耐力的影响而引起的基本挑战尚未得到克服。在这项工作中，我们在实验上展示了基于RRAM的IMC逻辑概念，即使经过一百万个耐力周期，也对RRAM变异性具有很强的韧性。我们的工作依赖于内存侦察逻辑的概念的概括，我们通过多达16个平行设备（操作数）实验证明了它，这是RRAM内存中逻辑的新里程碑。此外，我们将IMC与多级别细胞编程相结合，并首次在实验中证明了基于IMC RRAM的MLC 2位加法器。
Crossbar arrays of resistive memories (RRAM) hold the promise of enabling In-Memory Computing (IMC), but essential challenges due to the impact of device imperfection and device endurance have yet to be overcome. In this work, we demonstrate experimentally an RRAM-based IMC logic concept with strong resilience to RRAM variability, even after one million endurance cycles. Our work relies on a generalization of the concept of in-memory Scouting Logic, and we demonstrate it experimentally with up to 16 parallel devices (operands), a new milestone for RRAM in-memory logic. Moreover, we combine IMC with Multi-Level-Cell programming and demonstrate experimentally, for the first time, an IMC RRAM-based MLC 2-bit adder.
