動態負載平衡在DSM系統中扮演了一個相當重要的角色，其在執行時期偵測系統狀態並予適度的工作調整，充分的共享各節點上的資源以提高執行效率。但是在早期的研究之中，大多數的設計都著眼於處理器資源的負載平衡，卻忽略不同的記憶體資源環境下，可能因為某些節點記憶體資源的缺乏而增加存取延遲時間，降低了程式執行時的平行度。為了解決這個問題，我們將記憶體資源因素納入負載平衡演算之中，考量該資源在執行時所增加的延遲影響，適當地安排各節點的工作量以減少節點閒置時的等待時間。我們在測試數據中可以明顯的看出，相較於僅考量單一資源的負載分散演算，同時考慮處理器與記憶體資源的負載平衡機制可以將節點的等待時間減到最小，獲得較高的執行平行度與系統效能改善，並且我們的負載平衡機制在額外負擔的部分也相當的小。

In the distributed shared memory system, load balancing plays an important role to improve system efficiency. It dynamically adjusts workload distribution by the runtime collected system information, and the goal is to share various resources among nodes. In the early days, many researches about load balancing focus on CPU resources but do not take memory resources into account. Without this consideration, the additional time may arise due to costly memory access latency in some nodes that are low memory resources, and then the parallelism of program execution is down. So we consider the affection of the memory resource in our load balancing design; that is to say, the mechanism arranges workload distribution by both CPU and memory resource consideration. In our results show that load balancing with memory resource consideration reduces the system waiting time to increase parallelism, and our design has better system improvement compared with that of only one resource consideration. We also show that the overhead is low in our design.

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