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Energy usage has been an important concern in recent research on online job scheduling, where processors are allowed to vary the speed dynamically so as to save energy whenever possible. Notice that providing good quality of service such as response time (flow time) and conserving energy are conflicting objectives. An interesting problem for scheduling is how to optimize an economic tradeoff of flow time and energy. To this end, the past two years have witnessed significant progress in the single-processor setting, and online algorithms with performance close to optimal have been obtained. In this paper we extend the study of optimizing the tradeoff between flow time and energy to the multi-processor setting. We derive and analyze a simple non-migratory online algorithm that makes use of the classified-round-robin (CRR) strategy to dispatch jobs. Even in the worst case, its performance is within O(log P) times of the optimal migratory offline algorithm, where P is the ratio of the maximum job size to the minimum job size. Technically speaking, this online result stems from a non-trivial solution to an offline problem of eliminating migration, which is also interesting by itself.