This paper addresses nonclairvoyant and nonpreemptive online job scheduling in Grids. In the applied basic model, the Grid system consists of a large number of identical processor...
Uwe Schwiegelshohn, Andrei Tchernykh, Ramin Yahyap...
We describe and evaluate the performance of a parallel search engine that is able to cope efficiently with concurrent read/write operations. Read operations come in the usual form ...
In this paper, we investigate the use of parallelization in reinforcement learning (RL), with the goal of learning optimal policies for single-agent RL problems more quickly by us...
Granularity control is an effective means for trading power consumption with performance on dense shared memory multiprocessors, such as multi-SMT and multi-CMP systems. In this p...
Matthew Curtis-Maury, James Dzierwa, Christos D. A...
Reinforcement learning (RL) was originally proposed as a framework to allow agents to learn in an online fashion as they interact with their environment. Existing RL algorithms co...
Pascal Poupart, Nikos A. Vlassis, Jesse Hoey, Kevi...