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A Scalable GPU-Based Approach to Accelerate the Multiple-Choice Knapsack Problem
Linköpings universitet, Institutionen för datavetenskap, ESLAB - Laboratoriet för inbyggda system. Linköpings universitet, Tekniska högskolan.
Linköpings universitet, Institutionen för datavetenskap, ESLAB - Laboratoriet för inbyggda system. Linköpings universitet, Tekniska högskolan.
Linköpings universitet, Institutionen för datavetenskap, ESLAB - Laboratoriet för inbyggda system. Linköpings universitet, Tekniska högskolan.
2012 (engelsk)Inngår i: Design Automation and Test in Europe (DATE12) (short paper), Dresden, Germany, March 12-16, 2012., IEEE , 2012, s. 1126-1129Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Variants of the 0-1 knapsack problem manifest themselves at the core of several system-level optimization problems. The running times of such system-level optimization techniques are adversely affected because the knapsack problem is NP-hard. In this paper, we propose a new GPU-based approach to accelerate the multiple-choice knapsack problem, which is a general version of the 0-1 knapsack problem. Apart from exploiting the parallelism offered by the GPUs, we also employ a variety of GPU-specific optimizations to further accelerate the running times of the knapsack problem. Moreover, our technique is scalable in the sense that even when running large instances of the multiple-choice knapsack problems, we can efficiently utilize the GPU compute resources and memory bandwidth to achieve significant speedups.

sted, utgiver, år, opplag, sider
IEEE , 2012. s. 1126-1129
Serie
Design, Automation and Test in Europe, ISSN 1530-1591
HSV kategori
Identifikatorer
URN: urn:nbn:se:liu:diva-72206DOI: 10.1109/DATE.2012.6176665ISBN: 978-1-4577-2145-8 (tryckt)ISBN: 978-3-9810801-8-6 (tryckt)OAI: oai:DiVA.org:liu-72206DiVA, id: diva2:458268
Konferanse
Design Automation and Test in Europe (DATE12) (short paper), Dresden, Germany, March 12-16, 2012.
Tilgjengelig fra: 2011-11-22 Laget: 2011-11-22 Sist oppdatert: 2014-11-14

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