Von Neumann architecture based computers isolate/physically separate computation and storage units i.e. data is shuttled between computation unit (processor) and memory unit to realize logic/ arithmetic and storage functions. This to-and-fro movement of data leads to a fundamental limitation of modern computers, known as the memory wall. Logic in-Memory (LIM) approaches aim to address this bottleneck by computing inside the memory units and thereby eliminating the energy-intensive and time-consuming data movement. However, most LIM approaches reported in literature are not truly "simultaneous" as during LIM operation the bitcell can be used only as a Memory cell or only as a Logic cell. The bitcell is not capable of storing both the Memory/Logic outputs simultaneously. Here, we propose a novel 'Simultaneous Logic in-Memory' (SLIM) methodology that allows to implement both Memory and Logic operations simultaneously on the same bitcell in a non-destructive manner without losing the previously stored Memory state. Through extensive experiments we demonstrate the SLIM methodology using non-filamentary bilayer analog OxRAM devices with NMOS transistors (2T-1R bitcell). Detailed programming scheme, array level implementation and controller architecture are also proposed. Furthermore, to study the impact of introducing SLIM array in the memory hierarchy, a simple image processing application (edge detection) is also investigated. It has been estimated that by performing all computations inside the SLIM array, the total Energy Delay Product (EDP) reduces by ~ 40x in comparison to a modern-day computer. EDP saving owing to reduction in data transfer between CPU Memory is observed to be ~ 780x.

中文翻译：

---

SLIM：利用双层模拟 OxRAM 器件的同时内存逻辑计算

基于冯诺依曼架构的计算机将计算和存储单元隔离/物理分离，即数据在计算单元（处理器）和存储单元之间穿梭以实现逻辑/算术和存储功能。数据的这种来回移动导致了现代计算机的一个基本限制，即内存墙。内存中逻辑 (LIM) 方法旨在通过在内存单元内部进行计算来解决这一瓶颈，从而消除能源密集型和耗时的数据移动。然而，文献中报道的大多数 LIM 方法并不是真正的“同时”，因为在 LIM 操作期间，位单元只能用作存储器单元或仅用作逻辑单元。位单元不能同时存储两个内存/逻辑输出。在这里，我们提出了一本小说“内存中的同步逻辑” (SLIM) 方法，允许以非破坏性方式在同一位单元上同时实现内存和逻辑操作，而不会丢失先前存储的内存状态。通过大量实验，我们展示了使用具有 NMOS 晶体管（2T-1R 位单元）的非丝状双层模拟 OxRAM 器件的 SLIM 方法。还提出了详细的编程方案、阵列级实现和控制器架构。此外，为了研究在存储器层次结构中引入 SLIM 阵列的影响，还研究了一个简单的图像处理应用程序（边缘检测）。据估计，通过在 SLIM 阵列内执行所有计算，与现代计算机相比，总能量延迟积 (EDP) 减少了约 40 倍。