Abstract
3-D many-core processor (3-D MCP) has become an emerging technology to tackle the power wall problem due to rapidly increasing number of transistors. However, when maximizing the throughput of 3-D MCP, which is expressed as a weighted sum of the speeds, due to the inherent heat removal limitation, thermal issues must be taken into consideration. Since the temperature of a core strongly depends on its location in the 3-D IC, a proper task allocation can alleviate the thermal problem and improve the throughput. Nevertheless, conventional techniques require computationally intensive thermal simulation, which prohibits its usage from the online application. In this paper, we propose an efficient online task allocation and task migration algorithm attempting to maximize the throughput of 3-D MCP simultaneously, considering unfinished tasks left from the last scheduling interval and new incoming tasks of this scheduling interval. The results of our experiments show that our proposed method achieves a 20.82X runtime speedup. These results are comparable to the exhaustive solutions obtained from optimization-modeling software LINGO. In addition, on average, our throughput results, with and without consideration of unfinished tasks, are only 4.39% and 0.69% worse, respectively, than that of the exhaustive method. In 128 task-to-core allocations, our method takes only 0.951 ms, which is 59.39 times faster than that of the previous work. © 2014 IEEE.