A virtual memory based runtime to support multi-tenancy in clusters with GPUs. - Michela Becchi; Kittisak Sajjapongse; Ian Graves; Adam M. Procter; Vignesh T. Ravi; Srimat T. Chakradhar (HPDC, 2012)

A distributed CPU-GPU framework for pairwise alignments on large-scale sequence datasets. - Da Li 002; Kittisak Sajjapongse; Huan Truong; Gavin C. Conant; Michela Becchi (ASAP, 2013)

A preemption-based runtime to efficiently schedule multi-process applications on heterogeneous clusters with GPUs. - Kittisak Sajjapongse; Xiang Wang; Michela Becchi (HPDC, 2013)

A flexible scheduling framework for heterogeneous CPU-GPU clusters. - Kittisak Sajjapongse; Tejaswi Agarwal; Michela Becchi (HiPC, 2014)

Large-Scale Pairwise Alignments on GPU Clusters: Exploring the Implementation Space. - Huan Truong; Da Li 002; Kittisak Sajjapongse; Gavin C. Conant; Michela Becchi (J. Signal Process. Syst., 2014)

Improving Application Concurrency on GPUs by Managing Implicit and Explicit Synchronizations. - Michael Butler; Kittisak Sajjapongse; Michela Becchi (ICPADS, 2015)

IVM: a task-based shared memory programming model and runtime system to enable uniform access to CPU-GPU clusters. - Kittisak Sajjapongse; Ruidong Gu; Michela Becchi (Conf. Computing Frontiers, 2016)

Design and Implementation of Papyrus: Parallel Aggregate Persistent Storage. - Jungwon Kim; Kittisak Sajjapongse; Seyong Lee; Jeffrey S. Vetter (IPDPS, 2017)