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Modeling System Signal Integrity Dynamic to Achieve Optimal Memory Performance for DDR4 and Beyond

机译:建模系统信号完整性动态,实现DDR4及以后的最佳内存性能

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System memory performance is usually measured by the memory bandwidth, which is the speed of the memory IO interface (such as 3200Mbps for top speed DDR4) multiplied by the number of DQ signal that a system will support (such as 64 DQ bits). In addition to the bandwidth, the capacity of the memory system is also an important figure of merit. Memory array density in each DRAM is limited, therefore, multiple ranks and multiple DIMMs are often added to the system to increase system memory capacity. The effectiveness of quantifying memory bandwidth will need to take into account the actual data throughput. When a system has multiple ranks, the dynamic between the ranks is more complicated. Memory controller can issue a Read/Write from/to the same rank or from/to a different rank. Traditionally, empirical measurement from a real system can be tested to determine the optimal bus turnaround. This turnaround time is for the bus signal to settle. A violation will affect channel timing such as the pre-amble timing & causes data error. The turnaround time will directly impact the system effective bandwidth. The bandwidth efficiency is measured by the data throughput versus the total transaction duration. The efficiency will be estimated incorrectly if not considering the actual bus channel settling time of the system. This paper will present a modeling approach to cover the dynamics of system DDR bus turnaround. The DQ bus on the controller side and the DRAM is modeled with IO behavioral model which captures the On/Off timing. The On/Off states represent the driver mode and receive mode with on-die termination enabled. Details will be presented on how to handle the necessary feature for the modeling. This approach enables the prediction of bus channel dynamics, particularly in the case of turnaround signal integrity analysis. The method can equally apply to more complicated system configurations, such as multiple-rank DIMM systems, which often need to cover rank-to-rank switching between DIMMs. A validation system will be used to correlate this approach and will be presented in the paper.
机译:系统存储器性能通常是由存储器带宽,这是存储器IO接口(如为3200Mbps最高速度DDR4)乘以DQ信号,一个系统将支持(如64 DQ位)的数目的速度进行测定。除了带宽之外,存储器系统的容量也是一个重要的优点形态。每个DRAM中的内存阵列密度受到限制,因此,通常将多个等级和多个DIMM添加到系统中以增加系统存储器容量。量化内存带宽的有效性需要考虑实际的数据吞吐量。当系统具有多个级别时,排名之间的动态更加复杂。内存控制器可以从/到相同的等级或从/到不同的等级发出读/写。传统上,可以测试来自真实系统的经验测量,以确定最佳总线转机。这个周转时间是为了定居的总线信号。违规将影响信道时序,例如预先顺序定时并导致数据错误。周转时间将直接影响系统有效带宽。通过数据吞吐量与总交易持续时间相比测量带宽效率。如果不考虑系统的实际总线信道稳定时间,则估计效率是不正确的。本文将介绍一个建模方法,以涵盖系统DDR总线上转动态的模型方法。控制器侧的DQ总线和DRAM采用IO行为模型建模,捕获开/关定时。 ON / OFF状态表示启用导通终止的驱动程序模式和接收模式。详细信息将在如何处理建模的必要功能上。这种方法使得能够预测总线通道动态,特别是在旋转信号完整性分析的情况下。该方法同样可以应用于更复杂的系统配置,例如多级DIMM系统,这通常需要覆盖DIMM之间的秩对等级切换。验证系统将用于关联这种方法,并将在纸上呈现。

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