Compute-in-memory (CiM) is a promising approach to improving the computing speed and energy efficiency in dataintensive applications. Beyond existing CiM techniques of bitwise logic-in-memory operations and dot product operations, this paper extends the CiM paradigm with FAST, a new shift-based inmemory computation technique to handle high-concurrency operations on multiple rows in an SRAM. Such high-concurrency operations are widely seen in both conventional applications (e.g. the table update in a database), and emerging applications (e.g. the parallel weight update in neural network accelerators), in which low latency and low energy consumption are critical. The proposed shift-based CiM architecture is enabled by integrating the shifter function into each SRAM cell, and by creating a datapath that exploits the high-parallelism of shifting operations in multiple rows in the array. A 128-row 16-column shiftable SRAM in 65nm CMOS is designed to evaluate the proposed architecture. Postlayout SPICE simulations show average improvements of 4.4x energy efficiency and 96.0x speed over a conventional fully-digital memory-computing-separated scheme, when performing the 8-bit weight update task in a VGG-7 framework.
翻译:计算元模( CiM) 是提高数据密集应用中计算速度和能源效率的一个很有希望的方法。 除了现有比特逻辑模拟操作和点产品操作的CiM技术外,本文件还扩展了CiM模式,与FAST(一个新的基于转移的模拟计算技术)一起,后者是处理SRAM中多行高通货币操作的一个新的基于转换的模拟计算技术。这种高通货操作在常规应用(例如数据库中的表格更新)和新兴应用(例如神经网络加速器中的平行重量更新)中都非常关键,在这种应用中,低延缓度和低能源消耗是关键因素。拟议的基于转移的CimM结构之所以得以实现,是因为将转换功能纳入每个SRAM单元格,并创建一种数据路径,利用多行中高通货币移动操作的高度重复性。在65nm CMOS 中设计了128- 16行可移动的SRAM(SRAM) 以评价拟议的结构。 后置 SPICE 模拟显示4.4x的能源效率和8-GGF- GRAM- 全面更新常规格式任务框架时的平均改进。