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» Petascale computing with accelerators
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CVPR
2012
IEEE
11 years 11 months ago
Batch mode Adaptive Multiple Instance Learning for computer vision tasks
Multiple Instance Learning (MIL) has been widely exploited in many computer vision tasks, such as image retrieval, object tracking and so on. To handle ambiguity of instance label...
Wen Li, Lixin Duan, Ivor Wai-Hung Tsang, Dong Xu
ICCS
2009
Springer
13 years 6 months ago
Developing Scientific Applications with Loosely-Coupled Sub-tasks
The Simple API for Grid Applications (SAGA) can be used to develop a range of applications which are in turn composed of multiple sub-tasks. In particular SAGA is an effective tool...
Shantenu Jha, Yaakoub El Khamra, Joohyun Kim
IPPS
2009
IEEE
14 years 3 months ago
Power-aware dynamic task scheduling for heterogeneous accelerated clusters
Recent accelerators such as GPUs achieve better cost-performance and watt-performance ratio, while the range of their application is more limited than general CPUs. Thus heterogen...
Tomoaki Hamano, Toshio Endo, Satoshi Matsuoka
SC
2009
ACM
14 years 3 months ago
Leveraging 3D PCRAM technologies to reduce checkpoint overhead for future exascale systems
The scalability of future massively parallel processing (MPP) systems is being severely challenged by high failure rates. Current hard disk drive (HDD) checkpointing results in ov...
Xiangyu Dong, Naveen Muralimanohar, Norman P. Joup...
PVM
2009
Springer
14 years 3 months ago
MPI on a Million Processors
Petascale machines with close to a million processors will soon be available. Although MPI is the dominant programming model today, some researchers and users wonder (and perhaps e...
Pavan Balaji, Darius Buntinas, David Goodell, Will...