Abstract
In-memory computing systems have been attracting considerable attention as a method for servicing high-quality multimedia contents. In-memory computing was intended to store entire data sets in the main memory of a computer to eliminate the need to access slow mechanical hard discs and increase the ability to process complex and large volumes of data. Prior studies have proposed a dual inline memory module (DIMM) tree architecture (DTA) as a new structure for implementing the in-memory computing system. The DTA can apply a partitioned DIMM tree policy to efficiently manage memory. However, the partitioned DIMM tree has several drawbacks, including hardware overhead resulting from additional fields in both the translation lookaside buffer (TLB) and the page table and the demand for an additional fast partition area for the fast partition page table (FPPT). To overcome these drawbacks, this paper proposes an advanced TLB management policy for the partitioned DIMM tree, DIMM tree TLB and two new partitioned DIMM tree management policies, fast-FPPT and slow-FPPT. We model the proposed policies using C language and verify them by special workloads in experiments employing a large-capacity memory system. The experimental results show how the proposed policies influence system performance and confirm that they overcome problems in the existing DTA. The simulations revealed a similarity between the performance of systems using the proposed policies and that of the existing DTA model. However, as the proposed policies demand a considerably lower hardware cost than the existing DTA model, the proposed policies are more practical.
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