An online parallel CRC32 realization for Hybrid Memory Cube protocol

K. Salah
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引用次数: 1

Abstract

Hybrid Memory Cube (HMC) is a revolutionary standard in DRAM architecture based on 3D integration. It provides marvelous concurrency and reduced latency. HMC uses CRC32 for data integrity, but conventional Serial CRC calculation is very slow and has long latencies, here we propose three methods to implement parallel CRC to be very fast. The first method uses symbolic toolbox in MATLAB to generate the final equations of the CRC, and then these equations are exported to VERILOG so that we are able to calculate it in only one clock cycle. The second method is depending on using an existing tool that can generate parallel CRC but this tool has a limitation on the input data width as it is less than the maximum allowed data width in HMC which is 1152 bits, so we were able to find a work around method that enable us to calculate CRC32 for large data widthwith this tool. The third method is based on using the polynomial mathematics for CRC, as the CRC can be calculated using long division method. Method 1 latency is one clock cycle, Method 2 latency is 2 clock cycles, and method 3 latency is 37 clock cycles compared to serial CRC which latency is 1152 clock cycles.
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混合存储立方体协议的在线并行CRC32实现
混合内存立方体(HMC)是基于3D集成的DRAM架构中的革命性标准。它提供了惊人的并发性并减少了延迟。HMC使用CRC32来保证数据的完整性,但是传统的串行CRC计算速度很慢,并且有很长的延迟,在这里我们提出三种方法来实现并行CRC,以达到非常快的速度。第一种方法是利用MATLAB中的符号工具箱生成CRC的最终方程,然后将这些方程导出到VERILOG中,这样我们就可以在一个时钟周期内进行计算。第二种方法依赖于使用可以生成并行CRC的现有工具,但该工具对输入数据宽度有限制,因为它小于HMC中允许的最大数据宽度,即1152位,因此我们能够找到一种绕过方法,使我们能够使用该工具计算大数据宽度的CRC32。第三种方法基于对CRC的多项式数学,可以使用长除法计算CRC。与串行CRC的1152时钟周期相比,方法1的时延为1个时钟周期,方法2的时延为2个时钟周期,方法3的时延为37个时钟周期。
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