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ASG-VTS combines stochastic and energy-gradient techniques to simultaneously solve the slack distribution and task reordering problem. It produces very efficient results with few mode transitions. Our experiments show that ASG-VTS reduces number of mode transitions by 4.8 times compared to traditional energy-gradient-based approaches. Also, our heuristic algorithm can quickly find a solution that is as good as the optimal for a real-life GSM encoder\/decoder benchmark. The runtime of ASG-VTS is 150 times and 1034 times faster than energy-gradient based and optimal ILP algorithms, respectively. Since the runtime of ASG-VTS is very low, it is ideal for design space exploration in system-level design tools. We have also developed a web-based interface for ASG-VTS algorithm.\n          <\/jats:p>","DOI":"10.1145\/1278349.1278352","type":"journal-article","created":{"date-parts":[[2007,10,14]],"date-time":"2007-10-14T12:41:11Z","timestamp":1192365671000},"page":"39","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":7,"title":["Ultra-fast and efficient algorithm for energy optimization by gradient-based stochastic voltage and task scheduling"],"prefix":"10.1145","volume":"12","author":[{"given":"Bita","family":"Gorjiara","sequence":"first","affiliation":[{"name":"University of California, Irvine, CA, USA"}]},{"given":"Nader","family":"Bagherzadeh","sequence":"additional","affiliation":[{"name":"University of California, Irvine, CA, USA"}]},{"given":"Pai H.","family":"Chou","sequence":"additional","affiliation":[{"name":"University of California, Irvine, CA, USA and National Tsing Hua University, Taiwan"}]}],"member":"320","published-online":{"date-parts":[[2007,9]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"Abdi S. 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