Vipin Chaudhary

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As wireless sensor networks continue to grow, so does the need for effective security mechanisms. Because sensor networks may interact with sensitive data and/or operate in hostile unattended environments, it is imperative that these security concerns be addressed from the beginning of the system design. However, due to inherent resource and computing(More)
Datacenters are seeing unprecedented growth in recent years. The energy requirements to operate these large scale facilities are increasing significantly both in terms of operation cost as well as their indirect impact on ecology due to high carbon emissions. There are several ongoing research efforts towards the development of an integrated cloud(More)
In this paper we present the results of parallelizing two life sciences applications, Markov random fields-based (MRF) liver segmentation and HMMER's Viterbi algorithm, using GPUs. We relate our experiences in porting both applications to the GPU as well as the techniques and optimizations that are most beneficial. The unique characteristics of both(More)
Backbone anatomical structure detection and labeling is a necessary step for various analysis tasks of the vertebral column. Appearance, shape and geometry measurements are necessary for abnormality detection locally at each disc and vertebrae (such as herniation) as well as globally for the whole spine (such as spinal scoliosis). We propose a two-level(More)
As computational clusters increase in size, their mean time to failure reduces drastically. Typically, checkpointing is used to minimize the loss of computation. Most checkpointing techniques, however, require central storage for storing checkpoints. This results in a bottleneck and severely limits the scalability of checkpointing, while also proving to be(More)
Repeatable, quantitative assessment of intervertebral disc pathology requires accurate localization and labeling of the lumbar region discs. To that end, we propose a two-level probabilistic model for such disc localization and labeling. Our model integrates both pixel-level information, such as appearance, and object-level information, such as relative(More)
This paper describes a generic mechanism to migrate threads in heterogeneous distributed environments. To maintain high portability and flexibility, thread migration is implemented at language level. At compile-time, a preprocessor scans the C and C++ programs to build thread state, detects possible thread migration points, and transforms the source code(More)
Due to the ever-increasing size of sequence databases it has become clear that faster techniques must be employed to effectively perform biological sequence analysis in a reasonable amount of time. Exploiting the inherent parallelism between sequences is a common strategy. In this paper we enhance both the fine-grained and course-grained parallelism within(More)
HMMER, based on the profile Hidden Markov Model (HMM) is one of the most widely used sequence database searching tools, allowing researchers to compare HMMs to sequence databases or sequences to HMM databases. Such searches often take many hours and consume a great number of CPU cycles on modern computers. We present a cluster-enabled(More)
The mapping problem arises when the dependency structure of a parallel algorithm differs from the processor interconnection of the parallel computer or when the number of processes generated by the algorithm exceeds the number of processors available. The mapping problem (also known as task allocation) has been widely studied. We propose a new generalized(More)