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Monte-Carlo tree search (MCTS) combines the generality of stochastic simulation and the accuracy of tree search, which has attracted the great attention of scholars. However, the MCTS search requires a sufficient number of iterations to converge to a good solution, which is more difficult to optimize. In order to solve this problem, this paper presents a point-based incremental pruning (PIP) for Monte-Carlo...
This paper presents the first systematic study on co-scheduling independent jobs on integrated CPU-GPU systems with power caps considered. It reveals the performance degradations caused by the co-run contentions at the levels of both memory and power. It then examines the problem of using job co-scheduling to alleviate the degradations in this less understood scenario. It offers several algorithms...
In multiple-input multiple-output (MIMO) communication systems, complex matrix inversion is a very computationally demanding operation. Especially when the number of antennas increases, i.e., in a massive MIMO system, the complexity of matrix inversion becomes very high. Motivated by this observation, a new low complexity complex matrix inversion method, called SDF-SGR (Square root and Division Free...
We propose a resource allocation algorithm for OFDM system to provide QoS guarantee for unicast and multicast service concurrently. The optimization objective is to maximize the sum rate of the unicast service under the constraint of both the total power and the minimal rate provision of the multicast service, which can be solved by traditional two-step approach. To decrease the complexity, a greedy-based...
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