Conventional task scheduling on real-time systems with multiple processors is notorious for its computational intractability. This problem becomes even harder when designers also have to consider other constraints such as energy consumptions. Such a multi-objective trade-off exploration is a crucial step to generating cost-efficient real-time embedded systems. Although previous task schedulers have attempted to provide fast heuristics for design space exploration, they cannot handle large systems efficiently. As today's embedded systems become increasingly larger, the authors need a scalable scheduler to handle this complexity.