三維晶片(3D IC)逐漸變成一個重要的技術，因其具備晶片密度與異質整合彈性的優點，而多晶片處理器可以在達到同等效能的前提下消耗較少的功率，因此成為實現三維晶片的一個適合的應用，然而當提高三維多核心處理器的單位工作效能時，因為晶片內部熱散逸的效率限制，在設計上熱議題必須要被考量，此外晶片核心的溫度跟其在三維多核心處理器內部的位置有強烈的關係，一個正確的工作任務分配可以幫助減輕熱的問題同時可提高效能，在這篇文章中，我們針對三維多核心處理器，提出了一個熱導向的即時工作任務分配演算法，稱之為「漸近的任務分配演算法(Incremental Task Allocation; ITA)」。實驗結果將呈現此提出的演算法，相較於全解析演算法利用最佳化模型軟體LINGO，可達到16.32倍執行時間的加速，和23.18%單位工作效能的改善。平均而言，「漸近的任務分配演算法」只造成0.85%的單位工作效能減少。而在執行指派一百二十八個任務到一百二十八個核心的任務分配中，提出的演算法只需花費0.932微秒即可完成，相較與前人提出的演算法，執行時間加速了57.74倍。

Three-dimensional integrated circuit (3D IC) has become an emerging technology in view of its advantages in packing density and flexibility in heterogeneous integration. The multi-core processor (MCP), which is able to deliver equivalent performance with less power consumption, is a candidate for 3D implementation. However, when maximizing the throughput of 3D MCP, due to the inherent heat removal limitation, thermal issues must be taken into consideration. Furthermore, since the temperature of a core strongly depends on its location in the 3D MCP, a proper task allocation helps to alleviate any potential thermal problem and improve the throughput. In this paper, we present a thermal-aware on-line task allocation algorithm for 3D MCPs. The results of our experiments show that our proposed method achieves 16.32X runtime speedup, and 23.18% throughput improvement. These are comparable to the exhaustive solutions obtained from optimization modeling software LINGO. On average, our throughput is only 0.85% worse than that of the exhaustive method. In 128 task-to-core allocations, our method takes only 0.932 ms, which is 57.74 times faster than the previous work.