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首页> 外文期刊>IEEE Transactions on Computers >Crossbar-Constrained Technology Mapping for ReRAM Based In-Memory Computing
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Crossbar-Constrained Technology Mapping for ReRAM Based In-Memory Computing

机译:基于RERAM的内存计算的横杆约束技术映射

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摘要

In-memory computing has gained significant attention due to the potential for dramatic improvement in speed and energy. Redox-based resistive RAMs (ReRAMs), capable of non-volatile storage and logic operations simultaneously have been used for logic-in-memory computing approaches. To this effect, we propose ReRAM based VLIW Architecture for in-Memory comPuting (ReVAMP), supported by a detailed device-accurate simulation setup with peripheral circuitry. We present theoretical bounds on the minimum area required for in-memory computation of arbitrary Boolean functions specified using structural representation (And-Inverter Graph and Majority-Inverter Graph) and two-level representation (Exclusive-Sum-of-Product). To support the ReVAMP architecture, we present two technology mapping flows that fully exploit the bit-level parallelism offered by the execution of logic using ReRAM crossbar array. The area-constrained mapping (ArC) generates feasible mapping for a variety of crossbar dimensions while the delay-constrained mapping (DeC) focuses primarily on minimizing the latency of mapping. We evaluate the proposed mappings against two state-of-the-art technology in-memory computing architectures, PLiM and MAGIC along with their automation flows (SIMPLE and COMPACT). ArC and DeC outperform state-of-the-art PLiM architecture by 1:46x and 4:3x on average in latency. ArC offers significantly lower area (on average 25:27x and 6:57x), while improving the area-delay product by 1:37x and 1:12x against two mapping approaches for MAGIC respectively. In contrast, DeC achieves average area (1:45x and 3:06x) and area-delay product (1:12x and 6:36x) improvements over the mapping approaches for MAGIC architecture respectively. The proposed mapping techniques allow a variety of runtime efficiency trade-offs.
机译:由于速度和能量的巨大改善,内存计算已经显着。基于氧化还原的电阻RAM(RERAMS),能够同时用于逻辑内存计算方法的非易失性存储和逻辑操作。为此,我们提出了基于Reram的VLIW架构用于内存计算(Remamp),由具有外围电路的详细设备准确仿真设置支持。我们在使用结构表示(逆变器图形和多数逆变器图)和两级表示(独占方式)指定的任意布尔函数的内存内存计算所需的最小区域上的理论界限。为了支持Revamp架构,我们呈现了两个技术映射流,这些流程完全利用了使用Reram CrossBar阵列执行逻辑执行所提供的比特级并行性。区域约束映射(ARC)为各种横杆尺寸生成可行的映射,而延迟约束映射(DEC)主要集中在最小化映射的延迟上。我们评估拟议的映射,针对两种最先进的技术内存计算架构,对自动化流程(简单且紧凑)的魔法和魔法。 ARC和DEC优于最先进的PLIM架构1:46x和4:3x平均延迟。电弧提供明显更低的区域(平均为25:27倍和6:57倍),同时分别将区域延迟产品提高1:37X和1:12x,分别为两个映射魔法方法。相比之下,DEC将分别通过分别对魔法架构的映射方法进行平均面积(1:45x和3:06x)和面积延迟产品(1:12x和6:36x)。所提出的映射技术允许各种运行时间效率权衡。

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